Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM

	Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM
	Tang Minan 1; Zhang Kai 2; Liu Xing 2
	2018
发表期刊	Journal of Measurement Science and Instrumentation
ISSN	1674-8042
卷号	9 期号:1 页码:32-41
摘要	In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better, this paper proposes a combined forecasting model of passenger flow fluctuation range based on fuzzy information granulation and least squares support vector machine (LS-SVM) optimized by chaos particle swarm optimization (CPSO). Due to the nonlinearity and fluctuation of the passenger flow, firstly, fuzzy information granulation is used to extract the valid data from the window according to the requirement. Secondly, CPSO that has strong global search ability is applied to optimize the parameters of the LS-SVM forecasting model. Finally, the combined model is used to forecast the fluctuation range of early peak passenger flow at Tiyu Xilu Station of Guangzhou Metro Line 3 in 2014, and the results are compared and analyzed with other models. Simulation results demonstrate that the combined forecasting model can effectively track the fluctuation of passenger flow, which provides an effective method for predicting the fluctuation range of short-term passenger flow in the future.
关键词	urban rail transit passenger flow forecast least squares support vector machine (LS-SVM) fuzzy information granulation chaos particle swarm optimization(CPSO)
收录类别	CSCD
语种	英语
WOS研究方向	Transportation
WOS类目	TRANSPORTATION
CSCD记录号	CSCD:6208527
引用统计
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/73572
专题	兰州理工大学
作者单位	1.School of Automation and Electrical Engineering, Lanzhou Jiaotong University;;School of Mechanical and Electronical Engineering, Lanzhou University of Technology, ;;, Lanzhou;;Lanzhou, ;; 730070;;730050 2.School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China
第一作者单位	兰州理工大学
第一作者的第一单位	兰州理工大学
推荐引用方式 GB/T 7714	Tang Minan,Zhang Kai,Liu Xing. Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM[J]. Journal of Measurement Science and Instrumentation,2018,9(1):32-41.
APA	Tang Minan,Zhang Kai,&Liu Xing.(2018).Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM.Journal of Measurement Science and Instrumentation,9(1),32-41.
MLA	Tang Minan,et al."Combination forecast for urban rail transit passenger flow based on fuzzy information granulation and CPSO-LS-SVM".Journal of Measurement Science and Instrumentation 9.1(2018):32-41.