Passenger flow forecast for customized bus based on time series fuzzy clustering algorithm

Author:

Li Ming1,Wang Linlin2,Yang Jingfeng34,Zhang Zhenkun5,Zhang Nanfeng5,Xiang Yifei6,Zhou Handong78

Affiliation:

1. South China Agricultural University

2. Guangdong Lingnan Vocational and Technical College

3. Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences

4. Shenyang Institute of Automation Chinese Academy of Science

5. Guangzhou Customs District P.R. China laboratory

6. North China Electric Power University

7. Guangzhou Yuntu Information Technology Co, Ltd.

8. Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography

Abstract

Abstract Customized bus services are conducive to improving urban traffic and environment, and have attracted widespread attention. However, the problems encountered in the new customized bus mode include the large difference between the basis of customized bus passenger flow data analysis and the basis of the traditional bus passenger flow data analysis, and the difficulty in different vehicle scheduling caused by the combination of traditional and customized bus modes. We propose a customized bus passenger flow analysis algorithm and multi-destination customized bus line capacity scheduling algorithm, and display them in an intuitive way. The experimental results show that the algorithm model established in this paper can basically meet the data requirements of operation and management, and can provide decision support for customized bus line planning.

Publisher

John Benjamins Publishing Company

Subject

Human-Computer Interaction,Linguistics and Language,Animal Science and Zoology,Language and Linguistics,Communication

Reference18 articles.

1. Public Transit Planning and Operation

2. Research and demonstration application of Guangzhou custom bus operation management platform;He;Graduate thesis of South China University of Technology,2016

3. Research on the response strength of financial time series to public information based on Fuzzy Clustering;Li;Graduate thesis of Kunming University of Science and Technology,2011

4. A spatial-temporal estimation model of residual energy for pure electric buses based on traffic performance index;Li;Technical Gazette,2017

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