Scipediacontent: Scipediacontent moved page Draft Content 263039162 to 238,295nu

2021-03-23T01:45:15Z

Scipediacontent moved page Draft Content 263039162 to 238,295nu

Scipediacontent: Created page with " == Abstract == Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congesti..."

2021-03-23T01:43:33Z

Created page with " == Abstract == Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congesti..."

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== Abstract ==

Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congestion degrees using only vehicle speed. In this paper, we collect traffic flow information with three properties (traffic flow velocity, traffic flow density and traffic volume) of urban trunk roads, which is used to judge the traffic congestion degree. We first define a grey relational clustering model by leveraging grey relational analysis and rough set theory to mine relationships of multidimensional-attribute information. Then, we propose a grey relational membership degree rank clustering algorithm (GMRC) to discriminant clustering priority and further analyze the urban traffic congestion degree. Our experimental results show that the average accuracy of the GMRC algorithm is 24.9% greater than that of the K-means algorithm and 30.8% greater than that of the Fuzzy C-Means (FCM) algorithm. Furthermore, we find that our method can be more conducive to dynamic traffic warnings.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_263039162-beopen1385-8945-document.pdf</pdf>

== Original document ==

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

* [https://www.mdpi.com/2220-9964/5/5/71/pdf https://www.mdpi.com/2220-9964/5/5/71/pdf] under the license https://creativecommons.org/licenses/by

* [http://www.mdpi.com/2220-9964/5/5/71 http://www.mdpi.com/2220-9964/5/5/71],
: [https://doaj.org/toc/2220-9964 https://doaj.org/toc/2220-9964] under the license cc-by

* [http://www.mdpi.com/2220-9964/5/5/71/pdf http://www.mdpi.com/2220-9964/5/5/71/pdf],
: [http://dx.doi.org/10.3390/ijgi5050071 http://dx.doi.org/10.3390/ijgi5050071]

* [https://www.mdpi.com/2220-9964/5/5/71 https://www.mdpi.com/2220-9964/5/5/71],
: [https://www.mdpi.com/2220-9964/5/5/71/pdf https://www.mdpi.com/2220-9964/5/5/71/pdf],
: [https://dblp.uni-trier.de/db/journals/ijgi/ijgi5.html#ZhangYWM16 https://dblp.uni-trier.de/db/journals/ijgi/ijgi5.html#ZhangYWM16],
: [https://ui.adsabs.harvard.edu/abs/2016IJGI....5...71Z/abstract https://ui.adsabs.harvard.edu/abs/2016IJGI....5...71Z/abstract],
: [https://doi.org/10.3390/ijgi5050071 https://doi.org/10.3390/ijgi5050071],
: [https://core.ac.uk/display/89761819 https://core.ac.uk/display/89761819],
: [https://academic.microsoft.com/#/detail/2401757111 https://academic.microsoft.com/#/detail/2401757111] under the license https://creativecommons.org/licenses/by/4.0/

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238,295nu - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 263039162 to 238,295nu

Scipediacontent: Created page with " == Abstract == Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congesti..."