ºÝºÝߣshows by User: SarveshSingh10 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: SarveshSingh10 / Wed, 04 Feb 2015 11:10:39 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: SarveshSingh10 Multicriteria decison examination in electrical stystem /slideshow/multicriteria-decison-examination-in-electrical-stystem/44269638 multicriteriadecisonexaminationinelectricalstystem-150204111039-conversion-gate02
The process of a grid’s power monitoring and its system is quite complicated these days because a lot of variables and uncertainties contained in data. In this case, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining the state of the system and categorized into according to their level of safety. It helps system control operator to respond effectively according to their state of the system.]]>
The process of a grid’s power monitoring and its system is quite complicated these days because a lot of variables and uncertainties contained in data. In this case, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining the state of the system and categorized into according to their level of safety. It helps system control operator to respond effectively according to their state of the system.]]> Wed, 04 Feb 2015 11:10:39 GMT /slideshow/multicriteria-decison-examination-in-electrical-stystem/44269638 SarveshSingh10@slideshare.net(SarveshSingh10) Multicriteria decison examination in electrical stystem SarveshSingh10 The process of a grid’s power monitoring and its system is quite complicated these days because a lot of variables and uncertainties contained in data. In this case, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining the state of the system and categorized into according to their level of safety. It helps system control operator to respond effectively according to their state of the system. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/multicriteriadecisonexaminationinelectricalstystem-150204111039-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The process of a grid’s power monitoring and its system is quite complicated these days because a lot of variables and uncertainties contained in data. In this case, we use the Dominance-based Rough Set Approach (DRSA) to provide a set of rules for determining the state of the system and categorized into according to their level of safety. It helps system control operator to respond effectively according to their state of the system.
Multicriteria decison examination in electrical stystem from Sarvesh Singh
]]> 202 2 https://cdn.slidesharecdn.com/ss_thumbnails/multicriteriadecisonexaminationinelectricalstystem-150204111039-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Fault diagnosis in transformers /slideshow/transformers-final-version/44269361 transformersfinalversion-150204110339-conversion-gate02
Transformers are the vital parts of an electrical grid system. A faulty transformer can destabilize the electrical supply along with the other devices of the transmission system. Due to its significant role in the system, a transformer has to be free from faults and irregularities. Dissolved Gas-in-oil Analysis (DGA) is a method that helps in diagnosing the faults present in an electrical transformer. This paper proposes a hybrid system based on Genetic Neural Computing (GNC) for analyzing and interpreting the data derived from the concentration of the dissolved gases. It is further analyzed and clustered into four subsets according to the standard C57.104 defined by IEEE using genetic algorithm (GA). The clustered data is fed to the neural network that is used to predict the different types of faults present in the transformers. The hybrid system generates the necessary decision rules to assist the system’s operator in identifying the exact fault in the transformer and its fault status. This analysis would then be helpful in performing the required maintenance check and plan for repairs.]]>
Transformers are the vital parts of an electrical grid system. A faulty transformer can destabilize the electrical supply along with the other devices of the transmission system. Due to its significant role in the system, a transformer has to be free from faults and irregularities. Dissolved Gas-in-oil Analysis (DGA) is a method that helps in diagnosing the faults present in an electrical transformer. This paper proposes a hybrid system based on Genetic Neural Computing (GNC) for analyzing and interpreting the data derived from the concentration of the dissolved gases. It is further analyzed and clustered into four subsets according to the standard C57.104 defined by IEEE using genetic algorithm (GA). The clustered data is fed to the neural network that is used to predict the different types of faults present in the transformers. The hybrid system generates the necessary decision rules to assist the system’s operator in identifying the exact fault in the transformer and its fault status. This analysis would then be helpful in performing the required maintenance check and plan for repairs.]]> Wed, 04 Feb 2015 11:03:39 GMT /slideshow/transformers-final-version/44269361 SarveshSingh10@slideshare.net(SarveshSingh10) Fault diagnosis in transformers SarveshSingh10 Transformers are the vital parts of an electrical grid system. A faulty transformer can destabilize the electrical supply along with the other devices of the transmission system. Due to its significant role in the system, a transformer has to be free from faults and irregularities. Dissolved Gas-in-oil Analysis (DGA) is a method that helps in diagnosing the faults present in an electrical transformer. This paper proposes a hybrid system based on Genetic Neural Computing (GNC) for analyzing and interpreting the data derived from the concentration of the dissolved gases. It is further analyzed and clustered into four subsets according to the standard C57.104 defined by IEEE using genetic algorithm (GA). The clustered data is fed to the neural network that is used to predict the different types of faults present in the transformers. The hybrid system generates the necessary decision rules to assist the system’s operator in identifying the exact fault in the transformer and its fault status. This analysis would then be helpful in performing the required maintenance check and plan for repairs. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/transformersfinalversion-150204110339-conversion-gate02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Transformers are the vital parts of an electrical grid system. A faulty transformer can destabilize the electrical supply along with the other devices of the transmission system. Due to its significant role in the system, a transformer has to be free from faults and irregularities. Dissolved Gas-in-oil Analysis (DGA) is a method that helps in diagnosing the faults present in an electrical transformer. This paper proposes a hybrid system based on Genetic Neural Computing (GNC) for analyzing and interpreting the data derived from the concentration of the dissolved gases. It is further analyzed and clustered into four subsets according to the standard C57.104 defined by IEEE using genetic algorithm (GA). The clustered data is fed to the neural network that is used to predict the different types of faults present in the transformers. The hybrid system generates the necessary decision rules to assist the system’s operator in identifying the exact fault in the transformer and its fault status. This analysis would then be helpful in performing the required maintenance check and plan for repairs.
Fault diagnosis in transformers from Sarvesh Singh
]]> 1525 10 https://cdn.slidesharecdn.com/ss_thumbnails/transformersfinalversion-150204110339-conversion-gate02-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Improving circuit miniaturization and its efficiency using Rough Set Theory( A machine learning approach ) /slideshow/improving-circuit-miniaturization-and-its-efficiency-using-rough-set-theory/31176113 improvingcircuitminiaturizationanditsefficiencyusingroughsettheory-140213102843-phpapp01
A theoretical approach based on Rough Set Theory for Electronic Circuit miniaturization ]]>
A theoretical approach based on Rough Set Theory for Electronic Circuit miniaturization ]]> Thu, 13 Feb 2014 10:28:43 GMT /slideshow/improving-circuit-miniaturization-and-its-efficiency-using-rough-set-theory/31176113 SarveshSingh10@slideshare.net(SarveshSingh10) Improving circuit miniaturization and its efficiency using Rough Set Theory( A machine learning approach ) SarveshSingh10 A theoretical approach based on Rough Set Theory for Electronic Circuit miniaturization <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/improvingcircuitminiaturizationanditsefficiencyusingroughsettheory-140213102843-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A theoretical approach based on Rough Set Theory for Electronic Circuit miniaturization
Improving circuit miniaturization and its efficiency using Rough Set Theory( A machine learning approach ) from Sarvesh Singh
]]> 667 4 https://cdn.slidesharecdn.com/ss_thumbnails/improvingcircuitminiaturizationanditsefficiencyusingroughsettheory-140213102843-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-SarveshSingh10-48x48.jpg?cb=1529417160 I am currently pursuing my bachelors in Electronics and Instrumentation from VIT university. I am working in domain of Electrical and related field using Artificial Intelligence and machine learning techniques.. I am crazy about music,movies and mostly prefer to stay in the lap of nature and love animals.. https://cdn.slidesharecdn.com/ss_thumbnails/multicriteriadecisonexaminationinelectricalstystem-150204111039-conversion-gate02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/multicriteria-decison-examination-in-electrical-stystem/44269638 Multicriteria decison ... https://cdn.slidesharecdn.com/ss_thumbnails/transformersfinalversion-150204110339-conversion-gate02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/transformers-final-version/44269361 Fault diagnosis in tra... https://cdn.slidesharecdn.com/ss_thumbnails/improvingcircuitminiaturizationanditsefficiencyusingroughsettheory-140213102843-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/improving-circuit-miniaturization-and-its-efficiency-using-rough-set-theory/31176113 Improving circuit mini...