�ݺ�ߣshows by User: ijcsa

�ݺ�ߣshows by User: ijcsa / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ijcsa / Thu, 21 May 2020 04:40:23 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ijcsa 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) /ijcsa/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-234390799 natap202020209-200521044023
3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects]]>
3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects]]> Thu, 21 May 2020 04:40:23 GMT /ijcsa/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-234390799 ijcsa@slideshare.net(ijcsa) 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) ijcsa 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/natap202020209-200521044023-thumbnail.jpg?width=120&height=120&fit=bounds" /> 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects

3rd International Conference on Natural Language Processing and Trends (NATAP 2020) from ijcsa

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0 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) /slideshow/8th-international-conference-on-foundations-of-computer-science-technology-fcst-2020-232414878/232414878 fcst2020-200422103320
8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances.]]>
8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances.]]> Wed, 22 Apr 2020 10:33:20 GMT /slideshow/8th-international-conference-on-foundations-of-computer-science-technology-fcst-2020-232414878/232414878 ijcsa@slideshare.net(ijcsa) 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) ijcsa 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fcst2020-200422103320-thumbnail.jpg?width=120&height=120&fit=bounds" /> 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances.

8th International Conference on Foundations of Computer Science & Technology (FCST 2020) from ijcsa

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0 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) /slideshow/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-232045898/232045898 natap20204-200415092646
3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects.]]>
3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects.]]> Wed, 15 Apr 2020 09:26:46 GMT /slideshow/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-232045898/232045898 ijcsa@slideshare.net(ijcsa) 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) ijcsa 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/natap20204-200415092646-thumbnail.jpg?width=120&height=120&fit=bounds" /> 3rd International Conference on Natural Language Processing and Trends (NATAP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing. The Conference looks for significant contributions to all major fields of the Natural Language Computing in theoretical and practical aspects.

3rd International Conference on Natural Language Processing and Trends (NATAP 2020) from ijcsa

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0 VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHM /slideshow/video-segmentation-summarization-using-modified-genetic-algorithm-230964976/230964976 8518ijcsa01-200327120854
Video summarization of the segmented video is an essential process for video thumbnails, video surveillance and video downloading. Summarization deals with extracting few frames from each scene and creating a summary video which explains all course of action of full video with in short duration of time. The proposed research work discusses about the segmentation and summarization of the frames. A genetic algorithm (GA) for segmentation and summarization is required to view the highlight of an event by selecting few important frames required. The GA is modified to select only key frames for summarization and the comparison of modified GA is done with the GA.]]>
Video summarization of the segmented video is an essential process for video thumbnails, video surveillance and video downloading. Summarization deals with extracting few frames from each scene and creating a summary video which explains all course of action of full video with in short duration of time. The proposed research work discusses about the segmentation and summarization of the frames. A genetic algorithm (GA) for segmentation and summarization is required to view the highlight of an event by selecting few important frames required. The GA is modified to select only key frames for summarization and the comparison of modified GA is done with the GA.]]> Fri, 27 Mar 2020 12:08:54 GMT /slideshow/video-segmentation-summarization-using-modified-genetic-algorithm-230964976/230964976 ijcsa@slideshare.net(ijcsa) VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHM ijcsa Video summarization of the segmented video is an essential process for video thumbnails, video surveillance and video downloading. Summarization deals with extracting few frames from each scene and creating a summary video which explains all course of action of full video with in short duration of time. The proposed research work discusses about the segmentation and summarization of the frames. A genetic algorithm (GA) for segmentation and summarization is required to view the highlight of an event by selecting few important frames required. The GA is modified to select only key frames for summarization and the comparison of modified GA is done with the GA. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/8518ijcsa01-200327120854-thumbnail.jpg?width=120&height=120&fit=bounds" /> Video summarization of the segmented video is an essential process for video thumbnails, video surveillance and video downloading. Summarization deals with extracting few frames from each scene and creating a summary video which explains all course of action of full video with in short duration of time. The proposed research work discusses about the segmentation and summarization of the frames. A genetic algorithm (GA) for segmentation and summarization is required to view the highlight of an event by selecting few important frames required. The GA is modified to select only key frames for summarization and the comparison of modified GA is done with the GA.

VIDEO SEGMENTATION & SUMMARIZATION USING MODIFIED GENETIC ALGORITHM from ijcsa

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0 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) /slideshow/8th-international-conference-on-foundations-of-computer-science-technology-fcst-2020-230373463/230373463 fcst2020-200317055529
8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances]]>
8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances]]> Tue, 17 Mar 2020 05:55:29 GMT /slideshow/8th-international-conference-on-foundations-of-computer-science-technology-fcst-2020-230373463/230373463 ijcsa@slideshare.net(ijcsa) 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) ijcsa 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fcst2020-200317055529-thumbnail.jpg?width=120&height=120&fit=bounds" /> 8th International Conference on Foundations of Computer Science & Technology (FCST 2020) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Foundations of Computer Science & Technology. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advances

8th International Conference on Foundations of Computer Science & Technology (FCST 2020) from ijcsa

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0 A NEW EXTRACTION OPTIMIZATION APPROACH TO FREQUENT 2 ITEMSETS /slideshow/a-new-extraction-optimization-approach-to-frequent-2-itemsets-230331732/230331732 9219ijcsa01-200316112945
In this paper, we propose a new optimization approach to the APRIORI reference algorithm (AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We start by calculating the 1-itemets supports (cardinal 1 sets), then we prune the 1-itemsets not frequent and keep only those that are frequent (ie those with the item sets whose values are greater than or equal to a fixed minimum threshold). During the second iteration, we sort the frequent 1-itemsets in descending order of their respective supports and then we form the 2-itemsets. In this way the rules of association are discovered more quickly. Experimentally, the comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAX-MINER, shows its efficiency on weakly correlated data. Our work has also led to a classical model of side-by-side classification of items that we have obtained by establishing a relationship between the different sets of 2-itemsets.]]>
In this paper, we propose a new optimization approach to the APRIORI reference algorithm (AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We start by calculating the 1-itemets supports (cardinal 1 sets), then we prune the 1-itemsets not frequent and keep only those that are frequent (ie those with the item sets whose values are greater than or equal to a fixed minimum threshold). During the second iteration, we sort the frequent 1-itemsets in descending order of their respective supports and then we form the 2-itemsets. In this way the rules of association are discovered more quickly. Experimentally, the comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAX-MINER, shows its efficiency on weakly correlated data. Our work has also led to a classical model of side-by-side classification of items that we have obtained by establishing a relationship between the different sets of 2-itemsets.]]> Mon, 16 Mar 2020 11:29:45 GMT /slideshow/a-new-extraction-optimization-approach-to-frequent-2-itemsets-230331732/230331732 ijcsa@slideshare.net(ijcsa) A NEW EXTRACTION OPTIMIZATION APPROACH TO FREQUENT 2 ITEMSETS ijcsa In this paper, we propose a new optimization approach to the APRIORI reference algorithm (AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We start by calculating the 1-itemets supports (cardinal 1 sets), then we prune the 1-itemsets not frequent and keep only those that are frequent (ie those with the item sets whose values are greater than or equal to a fixed minimum threshold). During the second iteration, we sort the frequent 1-itemsets in descending order of their respective supports and then we form the 2-itemsets. In this way the rules of association are discovered more quickly. Experimentally, the comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAX-MINER, shows its efficiency on weakly correlated data. Our work has also led to a classical model of side-by-side classification of items that we have obtained by establishing a relationship between the different sets of 2-itemsets. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/9219ijcsa01-200316112945-thumbnail.jpg?width=120&height=120&fit=bounds" /> In this paper, we propose a new optimization approach to the APRIORI reference algorithm (AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We start by calculating the 1-itemets supports (cardinal 1 sets), then we prune the 1-itemsets not frequent and keep only those that are frequent (ie those with the item sets whose values are greater than or equal to a fixed minimum threshold). During the second iteration, we sort the frequent 1-itemsets in descending order of their respective supports and then we form the 2-itemsets. In this way the rules of association are discovered more quickly. Experimentally, the comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAX-MINER, shows its efficiency on weakly correlated data. Our work has also led to a classical model of side-by-side classification of items that we have obtained by establishing a relationship between the different sets of 2-itemsets.

A NEW EXTRACTION OPTIMIZATION APPROACH TO FREQUENT 2 ITEMSETS from ijcsa

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0 International conference on Advanced Natural Language Processing (AdNLP 2020) /slideshow/international-conference-on-advanced-natural-language-processing-adnlp-2020/229501335 onepagecfp-adnlp1-200302052201
International conference on Advanced Natural Language Processing (AdNLP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances.]]>
International conference on Advanced Natural Language Processing (AdNLP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances.]]> Mon, 02 Mar 2020 05:22:01 GMT /slideshow/international-conference-on-advanced-natural-language-processing-adnlp-2020/229501335 ijcsa@slideshare.net(ijcsa) International conference on Advanced Natural Language Processing (AdNLP 2020) ijcsa International conference on Advanced Natural Language Processing (AdNLP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/onepagecfp-adnlp1-200302052201-thumbnail.jpg?width=120&height=120&fit=bounds" /> International conference on Advanced Natural Language Processing (AdNLP 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its advances.

International conference on Advanced Natural Language Processing (AdNLP 2020) from ijcsa

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0 International Journal on Computational Science & Applications (IJCSA) /slideshow/international-journal-on-computational-science-applications-ijcsa-228613553/228613553 ijcsa-cfp-200219071919
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]>
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]> Wed, 19 Feb 2020 07:19:19 GMT /slideshow/international-journal-on-computational-science-applications-ijcsa-228613553/228613553 ijcsa@slideshare.net(ijcsa) International Journal on Computational Science & Applications (IJCSA) ijcsa International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcsa-cfp-200219071919-thumbnail.jpg?width=120&height=120&fit=bounds" /> International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.

International Journal on Computational Science & Applications (IJCSA) from ijcsa

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0 Call for papers - 6th International Conference on Software Engineering (SOENG 2020) /ijcsa/call-for-papers-6th-international-conference-on-software-engineering-soeng-2020 soeng2020cfp-200214095935
6th International Conference on Software Engineering (SOENG 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas.]]>
6th International Conference on Software Engineering (SOENG 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas.]]> Fri, 14 Feb 2020 09:59:35 GMT /ijcsa/call-for-papers-6th-international-conference-on-software-engineering-soeng-2020 ijcsa@slideshare.net(ijcsa) Call for papers - 6th International Conference on Software Engineering (SOENG 2020) ijcsa 6th International Conference on Software Engineering (SOENG 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/soeng2020cfp-200214095935-thumbnail.jpg?width=120&height=120&fit=bounds" /> 6th International Conference on Software Engineering (SOENG 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas.

Call for papers - 6th International Conference on Software Engineering (SOENG 2020) from ijcsa

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0 International Journal on Computational Science & Applications (IJCSA) /slideshow/international-journal-on-computational-science-applications-ijcsa-227723858/227723858 ijcsa-cfp-200212050555
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]>
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]> Wed, 12 Feb 2020 05:05:55 GMT /slideshow/international-journal-on-computational-science-applications-ijcsa-227723858/227723858 ijcsa@slideshare.net(ijcsa) International Journal on Computational Science & Applications (IJCSA) ijcsa International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcsa-cfp-200212050555-thumbnail.jpg?width=120&height=120&fit=bounds" /> International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.

International Journal on Computational Science & Applications (IJCSA) from ijcsa

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0 International Conference on Natural Language Processing and Machine Learning (NLPML 2020) /slideshow/international-conference-on-natural-language-processing-and-machine-learning-nlpml-2020-210320438/210320438 nlpmlcfp-191225072101
International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning.]]>
International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning.]]> Wed, 25 Dec 2019 07:21:01 GMT /slideshow/international-conference-on-natural-language-processing-and-machine-learning-nlpml-2020-210320438/210320438 ijcsa@slideshare.net(ijcsa) International Conference on Natural Language Processing and Machine Learning (NLPML 2020) ijcsa International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nlpmlcfp-191225072101-thumbnail.jpg?width=120&height=120&fit=bounds" /> International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning.

International Conference on Natural Language Processing and Machine Learning (NLPML 2020) from ijcsa

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0 International Conference on Natural Language Processing and Machine Learning (NLPML 2020) /slideshow/international-conference-on-natural-language-processing-and-machine-learning-nlpml-2020/192706714 nlpmlcfp-191112112254
International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning. The Conference looks for significant contributions to all major fields of the Natural Language processing and machine learning in theoretical and practical aspects.]]>
International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning. The Conference looks for significant contributions to all major fields of the Natural Language processing and machine learning in theoretical and practical aspects.]]> Tue, 12 Nov 2019 11:22:53 GMT /slideshow/international-conference-on-natural-language-processing-and-machine-learning-nlpml-2020/192706714 ijcsa@slideshare.net(ijcsa) International Conference on Natural Language Processing and Machine Learning (NLPML 2020) ijcsa International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning. The Conference looks for significant contributions to all major fields of the Natural Language processing and machine learning in theoretical and practical aspects. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/nlpmlcfp-191112112254-thumbnail.jpg?width=120&height=120&fit=bounds" /> International Conference on Natural Language Processing and Machine Learning (NLPML 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and Machine learning. The Conference looks for significant contributions to all major fields of the Natural Language processing and machine learning in theoretical and practical aspects.

International Conference on Natural Language Processing and Machine Learning (NLPML 2020) from ijcsa

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0 Partition Sort Revisited: Reconfirming the Robustness in Average Case and Much More /slideshow/partition-sort-revisited-reconfirming-the-robustness-in-average-case-and-much-more-175397614/175397614 2112ijcsa02-190924051949
In our previous work there was some indication that Partition Sort could be having a more robust average case O(nlogn) complexity than the popular Quick sort. In our first study in this paper, we reconfirm this through computer experiments for inputs from Cauchy distribution for which expectation theoretically does not exist. Additionally, the algorithm is found to be sensitive to parameters of the input probability distribution demanding further investigation on parameterized complexity. The results on this algorithm for Binomial inputs in our second study are very encouraging in that direction.]]>
In our previous work there was some indication that Partition Sort could be having a more robust average case O(nlogn) complexity than the popular Quick sort. In our first study in this paper, we reconfirm this through computer experiments for inputs from Cauchy distribution for which expectation theoretically does not exist. Additionally, the algorithm is found to be sensitive to parameters of the input probability distribution demanding further investigation on parameterized complexity. The results on this algorithm for Binomial inputs in our second study are very encouraging in that direction.]]> Tue, 24 Sep 2019 05:19:49 GMT /slideshow/partition-sort-revisited-reconfirming-the-robustness-in-average-case-and-much-more-175397614/175397614 ijcsa@slideshare.net(ijcsa) Partition Sort Revisited: Reconfirming the Robustness in Average Case and Much More ijcsa In our previous work there was some indication that Partition Sort could be having a more robust average case O(nlogn) complexity than the popular Quick sort. In our first study in this paper, we reconfirm this through computer experiments for inputs from Cauchy distribution for which expectation theoretically does not exist. Additionally, the algorithm is found to be sensitive to parameters of the input probability distribution demanding further investigation on parameterized complexity. The results on this algorithm for Binomial inputs in our second study are very encouraging in that direction. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa02-190924051949-thumbnail.jpg?width=120&height=120&fit=bounds" /> In our previous work there was some indication that Partition Sort could be having a more robust average case O(nlogn) complexity than the popular Quick sort. In our first study in this paper, we reconfirm this through computer experiments for inputs from Cauchy distribution for which expectation theoretically does not exist. Additionally, the algorithm is found to be sensitive to parameters of the input probability distribution demanding further investigation on parameterized complexity. The results on this algorithm for Binomial inputs in our second study are very encouraging in that direction.

Partition Sort Revisited: Reconfirming the Robustness in Average Case and Much More from ijcsa

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0 Inverted File Based Search Technique for Video Copy Retrieval /slideshow/inverted-file-based-search-technique-for-video-copy-retrieval/173358706 2112ijcsa03-190918112231
A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It aims to find whether a query video segment is a copy of video from the video database or not based on the signature of the video. It is hard to find whether a video is a copied video or a similar video since the features of the content are very similar from one video to the other. The main focus is to detect that the query video is present in the video database with robustness depending on the content of video and also by fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the image content of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the next step is to find the presence of copy of a query video in a video database, in which a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-file-based method.]]>
A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It aims to find whether a query video segment is a copy of video from the video database or not based on the signature of the video. It is hard to find whether a video is a copied video or a similar video since the features of the content are very similar from one video to the other. The main focus is to detect that the query video is present in the video database with robustness depending on the content of video and also by fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the image content of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the next step is to find the presence of copy of a query video in a video database, in which a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-file-based method.]]> Wed, 18 Sep 2019 11:22:31 GMT /slideshow/inverted-file-based-search-technique-for-video-copy-retrieval/173358706 ijcsa@slideshare.net(ijcsa) Inverted File Based Search Technique for Video Copy Retrieval ijcsa A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It aims to find whether a query video segment is a copy of video from the video database or not based on the signature of the video. It is hard to find whether a video is a copied video or a similar video since the features of the content are very similar from one video to the other. The main focus is to detect that the query video is present in the video database with robustness depending on the content of video and also by fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the image content of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the next step is to find the presence of copy of a query video in a video database, in which a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-file-based method. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa03-190918112231-thumbnail.jpg?width=120&height=120&fit=bounds" /> A video copy detection system is a content-based search engine focusing on Spatio-temporal features. It aims to find whether a query video segment is a copy of video from the video database or not based on the signature of the video. It is hard to find whether a video is a copied video or a similar video since the features of the content are very similar from one video to the other. The main focus is to detect that the query video is present in the video database with robustness depending on the content of video and also by fast search of fingerprints. The Fingerprint Extraction Algorithm and Fast Search Algorithm are adopted to achieve robust, fast, efficient and accurate video copy detection. As a first step, the Fingerprint Extraction algorithm is employed which extracts a fingerprint through the features from the image content of video. The images are represented as Temporally Informative Representative Images (TIRI). Then the next step is to find the presence of copy of a query video in a video database, in which a close match of its fingerprint in the corresponding fingerprint database is searched using inverted-file-based method.

Inverted File Based Search Technique for Video Copy Retrieval from ijcsa

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0 Call for papers - International Journal on Computational Science & Applications (IJCSA) /slideshow/call-for-papers-international-journal-on-computational-science-applications-ijcsa/170236164 ijcsa-170216120142-190909103607
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]>
International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.]]> Mon, 09 Sep 2019 10:36:07 GMT /slideshow/call-for-papers-international-journal-on-computational-science-applications-ijcsa/170236164 ijcsa@slideshare.net(ijcsa) Call for papers - International Journal on Computational Science & Applications (IJCSA) ijcsa International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ijcsa-170216120142-190909103607-thumbnail.jpg?width=120&height=120&fit=bounds" /> International Journal on Computational Science & Applications (IJCSA) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Computational Science & Applications. Computational science is interdisciplinary fields in which mathematical models are combined with scientific computing methods to study of a wide range of problems in science and engineering. Modeling and simulation tools find increasing applications not only in fundamental research, but also in real-world design and industry applications.

Call for papers - International Journal on Computational Science & Applications (IJCSA) from ijcsa

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0 Sliding Mode Controller Design for Hybrid Synchronization of Hyperchaotic Chen Systems /slideshow/sliding-mode-controller-design-for-hybrid-synchronization-of-hyperchaotic-chen-systems/169260681 2112ijcsa04-190905121110
This paper derives new results for the design of sliding mode controller for the hybrid synchronization of identical hyperchaotic Chen systems (Jia, Dai and Hui, 2010). The synchronizer results derived in this paper for the hybrid synchronization of identical hyperchaotic Chen systems are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve hybrid synchronization of the identical hyperchaotic Chen systems. Numerical simulations are shown to illustrate and validate the hybrid synchronization schemes derived in this paper for the identical hyperchaotic Chen systems.]]>
This paper derives new results for the design of sliding mode controller for the hybrid synchronization of identical hyperchaotic Chen systems (Jia, Dai and Hui, 2010). The synchronizer results derived in this paper for the hybrid synchronization of identical hyperchaotic Chen systems are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve hybrid synchronization of the identical hyperchaotic Chen systems. Numerical simulations are shown to illustrate and validate the hybrid synchronization schemes derived in this paper for the identical hyperchaotic Chen systems.]]> Thu, 05 Sep 2019 12:11:10 GMT /slideshow/sliding-mode-controller-design-for-hybrid-synchronization-of-hyperchaotic-chen-systems/169260681 ijcsa@slideshare.net(ijcsa) Sliding Mode Controller Design for Hybrid Synchronization of Hyperchaotic Chen Systems ijcsa This paper derives new results for the design of sliding mode controller for the hybrid synchronization of identical hyperchaotic Chen systems (Jia, Dai and Hui, 2010). The synchronizer results derived in this paper for the hybrid synchronization of identical hyperchaotic Chen systems are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve hybrid synchronization of the identical hyperchaotic Chen systems. Numerical simulations are shown to illustrate and validate the hybrid synchronization schemes derived in this paper for the identical hyperchaotic Chen systems. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa04-190905121110-thumbnail.jpg?width=120&height=120&fit=bounds" /> This paper derives new results for the design of sliding mode controller for the hybrid synchronization of identical hyperchaotic Chen systems (Jia, Dai and Hui, 2010). The synchronizer results derived in this paper for the hybrid synchronization of identical hyperchaotic Chen systems are established using Lyapunov stability theory. Since the Lyapunov exponents are not required for these calculations, the sliding mode control method is very effective and convenient to achieve hybrid synchronization of the identical hyperchaotic Chen systems. Numerical simulations are shown to illustrate and validate the hybrid synchronization schemes derived in this paper for the identical hyperchaotic Chen systems.

Sliding Mode Controller Design for Hybrid Synchronization of Hyperchaotic Chen Systems from ijcsa

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0 A Proposal on Social Tagging Systems Using Tensor Reduction and Controlling Requests /slideshow/a-proposal-on-social-tagging-systems-using-tensor-reduction-and-controlling-requests/164211735 2112ijcsa05-190816053323
Social Tagging System is the process in which user makes their interest by tagging on a particular item. These STS are in associated with web 2.0 and has sourceful information for the users with their recommendations. It provides different types of recommendations are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the KernelSVD smoothing technique. We provide now with the 4-order tensor approach, which we named as Tensor Reduction. Here the items that are tagged can be viewed by the user who are recommended the same item and tagged over it. There by can improve the social tagging recommendations efficiency and also the unwanted request has been controlled. The results show significant improvements in terms of effectiveness. ]]>
Social Tagging System is the process in which user makes their interest by tagging on a particular item. These STS are in associated with web 2.0 and has sourceful information for the users with their recommendations. It provides different types of recommendations are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the KernelSVD smoothing technique. We provide now with the 4-order tensor approach, which we named as Tensor Reduction. Here the items that are tagged can be viewed by the user who are recommended the same item and tagged over it. There by can improve the social tagging recommendations efficiency and also the unwanted request has been controlled. The results show significant improvements in terms of effectiveness. ]]> Fri, 16 Aug 2019 05:33:23 GMT /slideshow/a-proposal-on-social-tagging-systems-using-tensor-reduction-and-controlling-requests/164211735 ijcsa@slideshare.net(ijcsa) A Proposal on Social Tagging Systems Using Tensor Reduction and Controlling Requests ijcsa Social Tagging System is the process in which user makes their interest by tagging on a particular item. These STS are in associated with web 2.0 and has sourceful information for the users with their recommendations. It provides different types of recommendations are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the KernelSVD smoothing technique. We provide now with the 4-order tensor approach, which we named as Tensor Reduction. Here the items that are tagged can be viewed by the user who are recommended the same item and tagged over it. There by can improve the social tagging recommendations efficiency and also the unwanted request has been controlled. The results show significant improvements in terms of effectiveness. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa05-190816053323-thumbnail.jpg?width=120&height=120&fit=bounds" /> Social Tagging System is the process in which user makes their interest by tagging on a particular item. These STS are in associated with web 2.0 and has sourceful information for the users with their recommendations. It provides different types of recommendations are modeled by a 3-order tensor, on which multiway latent semantic analysis and dimensionality reduction is performed using both the Higher Order Singular Value Decomposition (HOSVD) method and the KernelSVD smoothing technique. We provide now with the 4-order tensor approach, which we named as Tensor Reduction. Here the items that are tagged can be viewed by the user who are recommended the same item and tagged over it. There by can improve the social tagging recommendations efficiency and also the unwanted request has been controlled. The results show significant improvements in terms of effectiveness.

A Proposal on Social Tagging Systems Using Tensor Reduction and Controlling Requests from ijcsa

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0 A New Active Learning Technique Using Furthest Nearest Neighbour Criterion for K-NN and SVM Classifiers /ijcsa/a-new-active-learning-technique-using-furthest-nearest-neighbour-criterion-for-knn-and-svm-classifiers 2112ijcsa06-190726105601
Active learning is a supervised learning method that is based on the idea that a machine learning algorithm can achieve greater accuracy with fewer labelled training images if it is allowed to choose the image from which it learns. Facial age classification is a technique to classify face images into one of the several predefined age groups. The proposed study applies an active learning approach to facial age classification which allows a classifier to select the data from which it learns. The classifier is initially trained using a small pool of labeled training images. This is achieved by using the bilateral two dimension linear discriminant analysis. Then the most informative unlabeled image is found out from the unlabeled pool using the furthest nearest neighbor criterion, labeled by the user and added to the appropriate class in the training set. The incremental learning is performed using an incremental version of bilateral two dimension linear discriminant analysis. This active learning paradigm is proposed to be applied to the k nearest neighbor classifier and the support vector machine classifier and to compare the performance of these two classifiers.]]>
Active learning is a supervised learning method that is based on the idea that a machine learning algorithm can achieve greater accuracy with fewer labelled training images if it is allowed to choose the image from which it learns. Facial age classification is a technique to classify face images into one of the several predefined age groups. The proposed study applies an active learning approach to facial age classification which allows a classifier to select the data from which it learns. The classifier is initially trained using a small pool of labeled training images. This is achieved by using the bilateral two dimension linear discriminant analysis. Then the most informative unlabeled image is found out from the unlabeled pool using the furthest nearest neighbor criterion, labeled by the user and added to the appropriate class in the training set. The incremental learning is performed using an incremental version of bilateral two dimension linear discriminant analysis. This active learning paradigm is proposed to be applied to the k nearest neighbor classifier and the support vector machine classifier and to compare the performance of these two classifiers.]]> Fri, 26 Jul 2019 10:56:01 GMT /ijcsa/a-new-active-learning-technique-using-furthest-nearest-neighbour-criterion-for-knn-and-svm-classifiers ijcsa@slideshare.net(ijcsa) A New Active Learning Technique Using Furthest Nearest Neighbour Criterion for K-NN and SVM Classifiers ijcsa Active learning is a supervised learning method that is based on the idea that a machine learning algorithm can achieve greater accuracy with fewer labelled training images if it is allowed to choose the image from which it learns. Facial age classification is a technique to classify face images into one of the several predefined age groups. The proposed study applies an active learning approach to facial age classification which allows a classifier to select the data from which it learns. The classifier is initially trained using a small pool of labeled training images. This is achieved by using the bilateral two dimension linear discriminant analysis. Then the most informative unlabeled image is found out from the unlabeled pool using the furthest nearest neighbor criterion, labeled by the user and added to the appropriate class in the training set. The incremental learning is performed using an incremental version of bilateral two dimension linear discriminant analysis. This active learning paradigm is proposed to be applied to the k nearest neighbor classifier and the support vector machine classifier and to compare the performance of these two classifiers. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa06-190726105601-thumbnail.jpg?width=120&height=120&fit=bounds" /> Active learning is a supervised learning method that is based on the idea that a machine learning algorithm can achieve greater accuracy with fewer labelled training images if it is allowed to choose the image from which it learns. Facial age classification is a technique to classify face images into one of the several predefined age groups. The proposed study applies an active learning approach to facial age classification which allows a classifier to select the data from which it learns. The classifier is initially trained using a small pool of labeled training images. This is achieved by using the bilateral two dimension linear discriminant analysis. Then the most informative unlabeled image is found out from the unlabeled pool using the furthest nearest neighbor criterion, labeled by the user and added to the appropriate class in the training set. The incremental learning is performed using an incremental version of bilateral two dimension linear discriminant analysis. This active learning paradigm is proposed to be applied to the k nearest neighbor classifier and the support vector machine classifier and to compare the performance of these two classifiers.

A New Active Learning Technique Using Furthest Nearest Neighbour Criterion for K-NN and SVM Classifiers from ijcsa

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0 Calculation of the Minimum Computational Complexity Based on Information Entropy /ijcsa/calculation-of-the-minimum-computational-complexity-based-on-information-entropy 2112ijcsa07-190719073033
In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on information entropy. The relationship between the minimum computational complexity and information entropy change is illustrated. A few examples are served as evidence of such connection. Meanwhile some basic rules of modeling problems are established. Finally, the nature of solving problems with computer programs is disclosed to support this theory and a redefinition of information entropy in this filed is proposed. This will develop a new field of science. ]]>
In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on information entropy. The relationship between the minimum computational complexity and information entropy change is illustrated. A few examples are served as evidence of such connection. Meanwhile some basic rules of modeling problems are established. Finally, the nature of solving problems with computer programs is disclosed to support this theory and a redefinition of information entropy in this filed is proposed. This will develop a new field of science. ]]> Fri, 19 Jul 2019 07:30:33 GMT /ijcsa/calculation-of-the-minimum-computational-complexity-based-on-information-entropy ijcsa@slideshare.net(ijcsa) Calculation of the Minimum Computational Complexity Based on Information Entropy ijcsa In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on information entropy. The relationship between the minimum computational complexity and information entropy change is illustrated. A few examples are served as evidence of such connection. Meanwhile some basic rules of modeling problems are established. Finally, the nature of solving problems with computer programs is disclosed to support this theory and a redefinition of information entropy in this filed is proposed. This will develop a new field of science. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa07-190719073033-thumbnail.jpg?width=120&height=120&fit=bounds" /> In order to find out the limiting speed of solving a specific problem using computer, this essay provides a method based on information entropy. The relationship between the minimum computational complexity and information entropy change is illustrated. A few examples are served as evidence of such connection. Meanwhile some basic rules of modeling problems are established. Finally, the nature of solving problems with computer programs is disclosed to support this theory and a redefinition of information entropy in this filed is proposed. This will develop a new field of science.

Calculation of the Minimum Computational Complexity Based on Information Entropy from ijcsa

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0 A Non-Revisiting Genetic Algorithm for Optimizing Numeric Multi-Dimensional Functions /slideshow/a-nonrevisiting-genetic-algorithm-for-optimizing-numeric-multidimensional-functions/154688293 2112ijcsa08-190710100353
Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major shortcomings of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that escorts to duplicate function evaluations which is a clear wastage of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of MultiDimensional numeric function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Furthermore, the recommended approach is not using any extra memory resources to avoid revisits. To analyze the influence of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions with two and four dimensions. The performance of the proposed genetic algorithm is superior as contrasted to simple genetic algorithm as confirmed by the experimental results. ]]>
Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major shortcomings of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that escorts to duplicate function evaluations which is a clear wastage of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of MultiDimensional numeric function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Furthermore, the recommended approach is not using any extra memory resources to avoid revisits. To analyze the influence of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions with two and four dimensions. The performance of the proposed genetic algorithm is superior as contrasted to simple genetic algorithm as confirmed by the experimental results. ]]> Wed, 10 Jul 2019 10:03:53 GMT /slideshow/a-nonrevisiting-genetic-algorithm-for-optimizing-numeric-multidimensional-functions/154688293 ijcsa@slideshare.net(ijcsa) A Non-Revisiting Genetic Algorithm for Optimizing Numeric Multi-Dimensional Functions ijcsa Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major shortcomings of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that escorts to duplicate function evaluations which is a clear wastage of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of MultiDimensional numeric function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Furthermore, the recommended approach is not using any extra memory resources to avoid revisits. To analyze the influence of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions with two and four dimensions. The performance of the proposed genetic algorithm is superior as contrasted to simple genetic algorithm as confirmed by the experimental results. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/2112ijcsa08-190710100353-thumbnail.jpg?width=120&height=120&fit=bounds" /> Genetic Algorithm (GA) is a robust and popular stochastic optimization algorithm for large and complex search spaces. The major shortcomings of Genetic Algorithms are premature convergence and revisits to individual solutions in the search space. In other words, Genetic algorithm is a revisiting algorithm that escorts to duplicate function evaluations which is a clear wastage of time and computational resources. In this paper, a non-revisiting genetic algorithm with adaptive mutation is proposed for the domain of MultiDimensional numeric function optimization. In this algorithm whenever a revisit occurs, the underlined search point is replaced with a mutated version of the best/random (chosen probabilistically) individual from the GA population. Furthermore, the recommended approach is not using any extra memory resources to avoid revisits. To analyze the influence of the method, the proposed non-revisiting algorithm is evaluated using nine benchmarks functions with two and four dimensions. The performance of the proposed genetic algorithm is superior as contrasted to simple genetic algorithm as confirmed by the experimental results.

A Non-Revisiting Genetic Algorithm for Optimizing Numeric Multi-Dimensional Functions from ijcsa

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0 https://cdn.slidesharecdn.com/profile-photo-ijcsa-48x48.jpg?cb=1590035934 https://cdn.slidesharecdn.com/ss_thumbnails/natap202020209-200521044023-thumbnail.jpg?width=320&height=320&fit=bounds ijcsa/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-234390799 3rd International Conf... https://cdn.slidesharecdn.com/ss_thumbnails/fcst2020-200422103320-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/8th-international-conference-on-foundations-of-computer-science-technology-fcst-2020-232414878/232414878 8th International Conf... https://cdn.slidesharecdn.com/ss_thumbnails/natap20204-200415092646-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/3rd-international-conference-on-natural-language-processing-and-trends-natap-2020-232045898/232045898 3rd International Conf...