Prediction of bus passenger trip flow based on artificial neural network
The bus passenger trip flow is the base data for transit route design and optimization, and the characteristic of urban land use is the important factor for transit trip. However, the standard land use data are difficult to reflect the intensity of transit trip. This research proposed a method based...
Main Authors: | Shaoqiang Yu, Caiyun Shang, Yang Yu, Shuyuan Zhang, Wenlong Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2016-10-01
|
Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1177/1687814016675999 |
Similar Items
-
Artificial Neural Networks for Forecasting Passenger Flows on Metro Lines
by: Mariano Gallo, et al.
Published: (2019-08-01) -
Predicting taxi passenger demand using artificial neural networks
by: Zander, Gustav
Published: (2017) -
A Comprehensive Comparative Analysis of the Basic Theory of the Short Term Bus Passenger Flow Prediction
by: Huawei Zhai, et al.
Published: (2018-08-01) -
Short-Term Prediction of Bus Passenger Flow Based on a Hybrid Optimized LSTM Network
by: Yong Han, et al.
Published: (2019-08-01) -
Applying Artificial Neural Networks to Forecast Passenger Flows of Metro Station Exits
by: Su, Yi-Hsuan, et al.
Published: (2010)