| Issue |
E3S Web Conf.
Volume 214, 2020
2020 International Conference on Energy Big Data and Low-carbon Development Management (EBLDM 2020)
|
|
|---|---|---|
| Article Number | 02035 | |
| Number of page(s) | 5 | |
| Section | Machine Learning and Energy Industry Structure Forecast Analysis | |
| DOI | https://doi.org/10.1051/e3sconf/202021402035 | |
| Published online | 07 December 2020 | |
Traffic demand Forecast of online car-hailing based on BP Neural Network
College of Management and Economy, Tianjin University Tianjin, China
To accurately predict passengers’ demand for ride-hailing, increase transport capacity in some areas directionally, make it easier for passengers to book ride-hailing, and thus enhance passengers’ travel experience, based on BP neural network model, combined with 2015-Mak-2019 ride-hailing demand change data, and based on MATLAB platform, the demand trend of 20202024 is forecasted. The results show that the demand for shared cars and rides will increase rapidly. Demand for shared bikes and taxis is rising slowly.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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