Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network
Joint Authors
Wu, Jin
Zhang, Shunfeng
Li, Peiqing
Zhong, Biqiang
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-16
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
This paper proposes an evaluation method based on a T-S fuzzy neural network for evaluating the speed grade of public-transport lines in the context of large-scale rail-transit planning and construction in Hangzhou.
The six-dimensional data of morning peak/evening peak average speed, average speed at peak, average station distance, proportion of dedicated lanes, and nonlinear coefficients were selected as input data for the neural network to output the operating speed grade of bus lines.
Improving and optimizing the membership function of the Takagi–Sugeno (T-S) model improves its predicted result accuracy compared to a traditional T-S model.
The line data of 28 typical trunk lines or expressways in Hangzhou were used as an example; the results demonstrate that the speed grade evaluation method based on an improved T-S fuzzy neural network can effectively and quickly evaluate the speed grade of Hangzhou public-transportation lines.
This paper presents a novel analysis and method for large-scale rail-transit planning and evaluation of urban public-transport lines.
The aim is to provide practical instruction for the subsequent optimization of public-transportation lines in Hangzhou.
American Psychological Association (APA)
Zhang, Shunfeng& Li, Peiqing& Zhong, Biqiang& Wu, Jin. 2020. Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1176401
Modern Language Association (MLA)
Zhang, Shunfeng…[et al.]. Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network. Journal of Advanced Transportation No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1176401
American Medical Association (AMA)
Zhang, Shunfeng& Li, Peiqing& Zhong, Biqiang& Wu, Jin. Speed Grade Evaluation of Public-Transportation Lines Based on an Improved T-S Fuzzy Neural Network. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1176401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176401