计算机科学 ›› 2010, Vol. 37 ›› Issue (10): 211-213.

• 人工智能 • 上一篇    下一篇

基于多智能计算算法融合的出行线路规划模型

马庆禄,刘卫宁,孙棣华,但雨芳   

  1. (重庆大学计算机学院 重庆400044)(重庆大学自动化学院 重庆400044)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家863计划项目(“重庆智能交通计算机集成管理控制与服务系统”,863-511-910-1031),重庆市科技攻关计划项目(CTSC, 2005AC6037)资助。

Analysis for Travel Route Planning Based on Fusion of Multi-intelligent Algorithm

MA Qing-lu,LIU Wei-ning,SUN Di-hua,DAN Yu-fang   

  • Online:2018-12-01 Published:2018-12-01

摘要: 为了使公众在出行前能事先根据出行道路的交通信息对出行线路进行整体规划设计,以便最大限度地降低能耗和拥堵时间,在研究人工神经网络算法的基础上,对用于解决旅行商问题(TSP)的进化算法进行了改进,引入了多种优秀的智能计算策略,以提高算法效率;并建立了新型群集智能分析模型,用以分析公众出行的线路规划问题。实验结果表明,改进的混合智能计算方法简易而有效,有助于克服算法选择的盲目性,进一步拓展了计算智能的研究方向。规划的出行线路能够满足城市居民出行信息服务的综合需要。

关键词: 出行信息服务,线路规划,神经网络,混合智能计算,群集智能模型

Abstract: In order that public can plan travel line before departure based on local traffic condition to short delay time and minimizing energy, this paper inmproved the evolutionary algorithm for Traveling Salesman Problem (TSP) based on artificial neural network,in which multi-intelligent computation algorithm is introduced to enhance the efficiency.And then a swarm intelligence analysis model was proposed to analyze the lines planning for public Traveling. The experimental results show that this method is simple and effective for calculating. It helps to overcome the blindness of choice to further expand in research direction of Computational Intelligence. And the results meet the needs of comprehensive travel information service for public.

Key words: Advanced traffic information service, Path planning, Neural networks, Hybrid intelligent computation,Swarm intelligence model

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!