Prediction Method of Bus Passenger Flow Based on RS-IPSOSVM
HUANG Yishao1,2, HAN Lei2,3
(1. Engineering Research Center of Catastrophic Prophylaxis and Treatment of Road & Traffic Safety, Ministry of Education,
Changsha University of Science & Technology, Changsha 410114, Hunan, China; 2. School of Traffic and
Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, Hunan, China;
3. Key Laboratory of Road & Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China)
Abstract:In order to improve the accuracy of bus passenger flow forecasting, based on bus IC card data, the variation law and the influencing factors of bus passenger flow were explored, and a prediction method of bus passenger flow based on rough set (RS), improved particle swarm optimization (IPSO) and support vector machine (SVM) was proposed. Firstly, the influencing factors of bus passenger flow were determined by deep mining of passenger flow data. Secondly, rough set was used to reduce the attributes of 13 initial influencing factors and eliminate redundant information to get 8 core influencing factors.Thirdly, the adaptive inertia weight and asynchronous learning factors were introduced to optimize the PSO algorithm, and the IPSO algorithm was used to find the global optimal parameters of the SVM. The kernel function was used to map the core influencing factors of bus passenger flow into high-dimensional space, and the nonlinear mapping relationship between the core influence factors and the bus passenger flow was fitted to realize the passenger flow prediction. Finally, the proposed method was verified by the data of bus passenger flow in Guangzhou. The results show that the prediction accuracy of the proposed method is above 90%, which simplifies the training samples, overcomes the blindness of SVM parameter selection, and effectively improves the practicability and reliability.
黄益绍1,2,韩磊2,3. 基于RS-IPSOSVM的公交客流量预测方法[J]. 重庆交通大学学报(自然科学版), 2020, 39(11): 11-19.
HUANG Yishao1,2, HAN Lei2,3. Prediction Method of Bus Passenger Flow Based on RS-IPSOSVM. Journal of Chongqing Jiaotong University(Natural Science), 2020, 39(11): 11-19.
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