際際滷shows by User: REddieWilson / http://www.slideshare.net/images/logo.gif 際際滷shows by User: REddieWilson / Sun, 29 Mar 2015 07:00:13 GMT 際際滷Share feed for 際際滷shows by User: REddieWilson Techniques for Inferring Mileage from the Department for Transport's MOT data set /slideshow/wilson-imperialseminar2015/46413986 wilsonimperialseminar2015-150329070013-conversion-gate01
My main purpose in this talk is try and convey a sense of my enthusiasm for mathematical modelling generally and how I've come to use it in a range of transport applications. For concreteness, I am going to talk in particular about work I have been doing on EPSRC grant EP/K000438/1 (PI: Jillian Anable, Aberdeen) where we are using the DfT's MOT data to estimate mileage totals and study how they are broken down across the population in various different ways. Embedded inside this practical problem is a whole set of miniature mathematical puzzles and challenges which are quite particular to the problem area itself, and one wider question which is rather deeper and more general: whether it is possible (and how) to convert usage data that is low-resolution in time but high-resolution in individuals to knowledge that is high-resolution in time but only expressed at a population level. This talk was a seminar to the CTS research group at Imperial College, 25th March 2015.]]>
My main purpose in this talk is try and convey a sense of my enthusiasm for mathematical modelling generally and how I've come to use it in a range of transport applications. For concreteness, I am going to talk in particular about work I have been doing on EPSRC grant EP/K000438/1 (PI: Jillian Anable, Aberdeen) where we are using the DfT's MOT data to estimate mileage totals and study how they are broken down across the population in various different ways. Embedded inside this practical problem is a whole set of miniature mathematical puzzles and challenges which are quite particular to the problem area itself, and one wider question which is rather deeper and more general: whether it is possible (and how) to convert usage data that is low-resolution in time but high-resolution in individuals to knowledge that is high-resolution in time but only expressed at a population level. This talk was a seminar to the CTS research group at Imperial College, 25th March 2015.]]> Sun, 29 Mar 2015 07:00:13 GMT /slideshow/wilson-imperialseminar2015/46413986 REddieWilson@slideshare.net(REddieWilson) Techniques for Inferring Mileage from the Department for Transport's MOT data set REddieWilson My main purpose in this talk is try and convey a sense of my enthusiasm for mathematical modelling generally and how I've come to use it in a range of transport applications. For concreteness, I am going to talk in particular about work I have been doing on EPSRC grant EP/K000438/1 (PI: Jillian Anable, Aberdeen) where we are using the DfT's MOT data to estimate mileage totals and study how they are broken down across the population in various different ways. Embedded inside this practical problem is a whole set of miniature mathematical puzzles and challenges which are quite particular to the problem area itself, and one wider question which is rather deeper and more general: whether it is possible (and how) to convert usage data that is low-resolution in time but high-resolution in individuals to knowledge that is high-resolution in time but only expressed at a population level. This talk was a seminar to the CTS research group at Imperial College, 25th March 2015. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wilsonimperialseminar2015-150329070013-conversion-gate01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> My main purpose in this talk is try and convey a sense of my enthusiasm for mathematical modelling generally and how I&#39;ve come to use it in a range of transport applications. For concreteness, I am going to talk in particular about work I have been doing on EPSRC grant EP/K000438/1 (PI: Jillian Anable, Aberdeen) where we are using the DfT&#39;s MOT data to estimate mileage totals and study how they are broken down across the population in various different ways. Embedded inside this practical problem is a whole set of miniature mathematical puzzles and challenges which are quite particular to the problem area itself, and one wider question which is rather deeper and more general: whether it is possible (and how) to convert usage data that is low-resolution in time but high-resolution in individuals to knowledge that is high-resolution in time but only expressed at a population level. This talk was a seminar to the CTS research group at Imperial College, 25th March 2015.
Techniques for Inferring Mileage from the Department for Transport's MOT data set from R. Eddie Wilson
]]> 316 5 https://cdn.slidesharecdn.com/ss_thumbnails/wilsonimperialseminar2015-150329070013-conversion-gate01-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-REddieWilson-48x48.jpg?cb=1500021155 I lead the University of Bristol's new Transport and Mobility Modelling research group. I am also head of the Department of Engineering Mathematics.