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Road and travel time cross-validation for urban modelling
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Crosby, Henry James, Damoulas, Theodoros and Jarvis, Stephen A. (2019) Road and travel time cross-validation for urban modelling. International Journal of Geographical Information Science, 34 (1). pp. 98-118. doi:10.1080/13658816.2019.1658876 ISSN 1362-3087.
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WRAP-Road-travel-time-cross-validation-urban-Damoulas-2019.pdf - Accepted Version - Requires a PDF viewer. Download (8Mb) | Preview |
Official URL: https://doi.org/10.1080/13658816.2019.1658876
Abstract
The physical and social processes in urban systems are inherently spatial and hence data describing them contain spatial autocorrelation (a proximity-based interdependency on a variable) that need to be accounted for. Standard k-fold cross-validation (KCV) techniques that attempt to measure the generalisation performance of machine learning and statistical algorithms are inappropriate in this setting due to their inherent i.i.d assumption, which is violated by spatial dependency. As such, more appropriate validation methods have been considered, notably blocking and spatial k-fold cross-validation (SKCV). However, the physical barriers and complex network structures which make up a city’s landscape mean that these methods are also inappropriate, largely because the travel patterns (and hence Spatial Autocorrelation (SAC)) in most urban spaces are rarely Euclidean in nature. To overcome this problem, we propose a new road distance and travel time k-fold cross-validation method, RT-KCV. We show how this outperforms the prior art in providing better estimates of the true generalisation performance to unseen data.
| Item Type: | Journal Article | |||||||||
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| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) H Social Sciences > HE Transportation and Communications Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science Faculty of Science, Engineering and Medicine > Science > Statistics |
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| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | Spatial data infrastructures, Spatial data mining , Travel time (Traffic engineering) -- , Travel time (Traffic engineering) -- Data processing, Euclidean algorithm | |||||||||
| Journal or Publication Title: | International Journal of Geographical Information Science | |||||||||
| Publisher: | Informa UK Limited | |||||||||
| ISSN: | 1362-3087 | |||||||||
| Official Date: | 29 August 2019 | |||||||||
| Dates: |
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| Volume: | 34 | |||||||||
| Number: | 1 | |||||||||
| Page Range: | pp. 98-118 | |||||||||
| DOI: | 10.1080/13658816.2019.1658876 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Reuse Statement (publisher, data, author rights): | “This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Geographical Information Science on 29/08/2019, available online: http://www.tandfonline.com/10.1080/13658816.2019.1658876 | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| Date of first compliant deposit: | 6 May 2020 | |||||||||
| Date of first compliant Open Access: | 29 August 2021 | |||||||||
| RIOXX Funder/Project Grant: |
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