| Issue |
E3S Web Conf.
Volume 261, 2021
2021 7th International Conference on Energy Materials and Environment Engineering (ICEMEE 2021)
|
|
|---|---|---|
| Article Number | 03052 | |
| Number of page(s) | 4 | |
| Section | Environmental Engineering Planning and Urban Facilities Construction | |
| DOI | https://doi.org/10.1051/e3sconf/202126103052 | |
| Published online | 21 May 2021 | |
Research on bus elastic departure interval based on Wavelet Neural Network
1
School of Information Engineering, Wuhan University of Technology, 430063 Wuhan, China
2
School of Information Engineering, Wuhan University of Technology, 430063 Wuhan, China
3
School of Information Engineering, Wuhan University of Technology, 430063 Wuhan, China
* Corresponding author: 214207358@qq.com
In recent years, more and more people choose to travel by bus to save time and economic costs, but the problem of inaccurate bus arrival has become increasingly prominent. The reason is the lack of scientific planning of departure time. This paper takes the passenger flow as an important basis for departure interval, proposes a passenger flow prediction method based on wavelet neural network, and uses intelligent optimization algorithm to study the bus elastic departure interval. In this paper, the wavelet neural network prediction model and the elastic departure interval optimization model are established, and then the model is solved by substituting the data, and finally the theoretical optimal departure interval is obtained.
© The Authors, published by EDP Sciences, 2021
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