Scipediacontent: Scipediacontent moved page Draft Content 381632761 to Harrod et al 2018a

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Scipediacontent moved page Draft Content 381632761 to Harrod et al 2018a

Scipediacontent: Created page with " == Abstract == italic>K-means clustering is employed to identify recurrent delay patterns on a high traffic railway line north of Copenhagen, Denmark. The clus..."

2021-02-15T08:53:48Z

Created page with " == Abstract == italic>K</jats:italic>-means clustering is employed to identify recurrent delay patterns on a high traffic railway line north of Copenhagen, Denmark. The clus..."

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== Abstract ==

italic>K-means clustering is employed to identify recurrent delay patterns on a high traffic railway line north of Copenhagen, Denmark. The clusters identify behavioral patterns in the very large (“big data”) datasets generated automatically and continuously by the railway signal system. The results reveal the conditions where corrective actions are necessary, showing the cases where recurrent delay patterns take place. Delay profiles and delay change profiles are generated from timestamps to compare different train runs and to partition the set of observations into groups of similar elements. K-means clustering can identify and discriminate different patterns affecting the same stations, which is otherwise difficult in previous approaches based on visual inspection. Classical methods of univariate analysis do not reveal these patterns. The demonstrated methodology is scalable and can be applied to any system of transport.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_381632761-beopen620-6910-document.pdf</pdf>

== Original document ==

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

* [http://downloads.hindawi.com/journals/jat/2018/6164534.pdf http://downloads.hindawi.com/journals/jat/2018/6164534.pdf] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.1155/2018/6164534 http://dx.doi.org/10.1155/2018/6164534] under the license cc-by

* [http://downloads.hindawi.com/journals/jat/2018/6164534.pdf http://downloads.hindawi.com/journals/jat/2018/6164534.pdf],
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: [http://dx.doi.org/10.1155/2018/6164534 http://dx.doi.org/10.1155/2018/6164534] under the license http://creativecommons.org/licenses/by/4.0

* [http://dx.doi.org/10.1155/2018/6164534 http://dx.doi.org/10.1155/2018/6164534],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://orbit.dtu.dk/en/publications/fa763871-1022-4edb-a740-fc2ea9ffb600 https://orbit.dtu.dk/en/publications/fa763871-1022-4edb-a740-fc2ea9ffb600],
: [https://doi.org/10.1155/2018/6164534 https://doi.org/10.1155/2018/6164534],
: [https://backend.orbit.dtu.dk/ws/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf https://backend.orbit.dtu.dk/ws/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf],
: [https://www.hindawi.com/journals/jat/aip/6164534 https://www.hindawi.com/journals/jat/aip/6164534]

* [https://www.hindawi.com/journals/jat/2018/6164534 https://www.hindawi.com/journals/jat/2018/6164534],
: [https://doi.org/10.1155/2018/6164534 https://doi.org/10.1155/2018/6164534],
: [https://orbit.dtu.dk/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf https://orbit.dtu.dk/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf],
: [http://downloads.hindawi.com/journals/jat/2018/6164534.pdf http://downloads.hindawi.com/journals/jat/2018/6164534.pdf],
: [https://backend.orbit.dtu.dk/ws/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf https://backend.orbit.dtu.dk/ws/files/146752428/JAT_Clustering_paper_MINOR_REVISION_v04_FINAL.pdf],
: [https://orbit.dtu.dk/en/publications/application-of-data-clustering-to-railway-delay-pattern-recogniti https://orbit.dtu.dk/en/publications/application-of-data-clustering-to-railway-delay-pattern-recogniti],
: [https://orbit.dtu.dk/en/publications/application-of-data-clustering-to-railway-delay-pattern-recognition(fa763871-1022-4edb-a740-fc2ea9ffb600).html https://orbit.dtu.dk/en/publications/application-of-data-clustering-to-railway-delay-pattern-recognition(fa763871-1022-4edb-a740-fc2ea9ffb600).html],
: [https://core.ac.uk/display/157777335 https://core.ac.uk/display/157777335],
: [https://academic.microsoft.com/#/detail/2801522993 https://academic.microsoft.com/#/detail/2801522993]

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Harrod et al 2018a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 381632761 to Harrod et al 2018a

Scipediacontent: Created page with " == Abstract == italic>K-means clustering is employed to identify recurrent delay patterns on a high traffic railway line north of Copenhagen, Denmark. The clus..."