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

IF 0.9 4区 心理学 Q3 COMMUNICATION
Ming Li, Linlin Wang, Jingfeng Yang, Zhenkun Zhang, Nanfeng Zhang, Yifei Xiang, Handong Zhou
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引用次数: 5

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.
基于时间序列模糊聚类算法的客流量预测
定制公交服务有利于改善城市交通和环境,受到广泛关注。然而,新的定制公交模式遇到的问题包括定制公交客流数据分析的基础与传统公交客流数据的分析基础差异较大,以及传统公交模式与定制公交模式相结合导致不同车辆调度困难。我们提出了一种定制公交客流分析算法和多目的地定制公交线路运力调度算法,并以直观的方式进行了展示。实验结果表明,本文建立的算法模型基本能够满足运营管理的数据需求,能够为定制公交线路规划提供决策支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.30
自引率
6.70%
发文量
8
期刊介绍: This international peer-reviewed journal aims to advance knowledge in the growing and strongly interdisciplinary area of Interaction Studies in biological and artificial systems. Understanding social behaviour and communication in biological and artificial systems requires knowledge of evolutionary, developmental and neurobiological aspects of social behaviour and communication; the embodied nature of interactions; origins and characteristics of social and narrative intelligence; perception, action and communication in the context of dynamic and social environments; social learning.
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