Scipediacontent: Scipediacontent moved page Draft Content 421485640 to Pavlyuk 2019a

2021-02-12T11:51:18Z

Scipediacontent moved page Draft Content 421485640 to Pavlyuk 2019a

Scipediacontent: Created page with " == Abstract == A spatiotemporal approach that simultaneously utilises both spatial and temporal relationships is gaining scientific interest in the field of traffic flow fo..."

2021-02-12T11:51:15Z

Created page with " == Abstract == A spatiotemporal approach that simultaneously utilises both spatial and temporal relationships is gaining scientific interest in the field of traffic flow fo..."

New page

== Abstract ==

A spatiotemporal approach that simultaneously utilises both spatial and temporal relationships is gaining scientific interest in the field of traffic flow forecasting. Accurate identification of the spatiotemporal structure (dependencies amongst traffic flows in space and time) plays a critical role in modern traffic forecasting methodologies, and recent developments of data-driven feature selection and extraction methods allow the identification of complex relationships. This paper systematically reviews studies that apply feature selection and extraction methods for spatiotemporal traffic forecasting. The reviewed bibliographic database includes 211 publications and covers the period from early 1984 to March 2018. A synthesis of bibliographic sources clarifies the advantages and disadvantages of different feature selection and extraction methods for learning the spatiotemporal structure and discovers trends in their applications. We conclude that there is a clear need for development of comprehensive guidelines for selecting appropriate spatiotemporal feature selection and extraction methods for urban traffic forecasting.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_421485640-beopen68-6437-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1186/s12544-019-0345-9 http://dx.doi.org/10.1186/s12544-019-0345-9] under the license https://creativecommons.org/licenses/by/4.0

* [https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0345-9 https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0345-9] under the license https://creativecommons.org/licenses/by/4.0

* [http://link.springer.com/article/10.1186/s12544-019-0345-9 http://link.springer.com/article/10.1186/s12544-019-0345-9],
: [https://doaj.org/toc/1867-0717 https://doaj.org/toc/1867-0717],
: [https://doaj.org/toc/1866-8887 https://doaj.org/toc/1866-8887] under the license cc-by

* [http://link.springer.com/content/pdf/10.1186/s12544-019-0345-9.pdf http://link.springer.com/content/pdf/10.1186/s12544-019-0345-9.pdf],
: [http://link.springer.com/article/10.1186/s12544-019-0345-9/fulltext.html http://link.springer.com/article/10.1186/s12544-019-0345-9/fulltext.html],
: [http://dx.doi.org/10.1186/s12544-019-0345-9 http://dx.doi.org/10.1186/s12544-019-0345-9]

* [https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0345-9 https://etrr.springeropen.com/track/pdf/10.1186/s12544-019-0345-9],
: [https://etrr.springeropen.com/articles/10.1186/s12544-019-0345-9 https://etrr.springeropen.com/articles/10.1186/s12544-019-0345-9],
: [https://link.springer.com/article/10.1186/s12544-019-0345-9 https://link.springer.com/article/10.1186/s12544-019-0345-9],
: [https://academic.microsoft.com/#/detail/2914716043 https://academic.microsoft.com/#/detail/2914716043] under the license https://creativecommons.org/licenses/by/4.0

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Pavlyuk 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 421485640 to Pavlyuk 2019a

Scipediacontent: Created page with " == Abstract == A spatiotemporal approach that simultaneously utilises both spatial and temporal relationships is gaining scientific interest in the field of traffic flow fo..."