原文传递
Short-Time Bus Route Passenger Flow Prediction Based on a Secondary Decomposition Integration Method
| 题名： | Short-Time Bus Route Passenger Flow Prediction Based on a Secondary Decomposition Integration Method |
| 正文语种： | eng |
| 作者： | Yuanping Li;Changxi Ma |
| 作者单位： | School of Traffic and Transportation Lanzhou Jiaotong Univ. Lanzhou 730070 China;School of Traffic and Transportation Lanzhou Jiaotong Univ. Lanzhou 730070 China |
| 关键词： | Bus route passenger flow forecast; Secondary decomposition integration; Empirical modal decomposition (EMD); Kernel extreme learning machine (KELM) |
| 摘要： | Bus passenger flow is one of the decisive factors for the development of public transportation. Therefore, accurate prediction of real-time passenger flow on bus routes not only helps bus companies to make reasonable scheduling plans to meet the travel needs of passengers but also promotes the sound development of urban public transportation and reduces pollution. In this paper, we propose a secondary decomposition integration method that combines empirical modal decomposition (EMD), sample entropy (SE), and kernel extreme learning machine (KELM) to achieve a short-time prediction of bus route passenger flow. The EMD decomposes the original passenger flow data into several intrinsic mode functions, measures the complexity of the decomposed intrinsic mode functions using SE, and performs a secondary decomposition of the intrinsic mode functions with the highest complexity using EMD, followed by the prediction of the two decomposition results using KELM. The final predicted result is the sum of the two results. The model is verified by the real card-swiping data of two bus lines per minute. Each group of data has 300 data, with 80% of the data as the training set and the remaining 20% as the test set, which can predict the passenger flow per minute. The experimental results show that the short-term bus passenger flow forecasting method proposed in this paper has high accuracy and good robustness. |
| 出版年： | 2023 |
| 期刊名称： | Journal of Transportation Engineering |
| 卷： | 149 |
| 期： | 2 |
| 页码： | 04022132.1-04022132.10 |
相关文献
- Real-time short turning strategy based on passenger choice behavior
- Measuring the Relationship between Influence Factor and Urban Rail Transit Passenger Flow: Correlation or Causality?
- Pattern-Based Time-Discretized Method for Bus Travel Time Prediction
- Novel Hybrid Spatiotemporal Convolution Neural Network Model for Short-Term Passenger Flow Prediction in a Large-Scale Metro System
- Prediction of Public Bus Passenger Flow Using Spatial-Temporal Hybrid Model of Deep Learning
- Improved Dynamic Time Warping Algorithm for Bus Route Trajectory Curve Fitting
检索历史
应用推荐
