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ID:31976519
大小:1.71 MB
页数:57页
时间:2019-01-29
《基于变异粒子群算法的公交线网分层优化-研究》由会员上传分享,免费在线阅读,更多相关内容在教育资源-天天文库。
1、兰州交通大学硕士学位论文skeletonlinesarebuilt,eachlayer’soptimizationconstraintsaredetermined,andthePSOalgorithmwithmutationisusedtofindthesolutionsforeachlayer,theoptimizationandsettingofthemainskeletonlinesandtheinferiorskeletonlinesarecompleted,thepracticalofthePSOalgorithmwithmutationan
2、dtheeffectivenessofhierarchicaloptimizationareverifiedbyanalyzingandcalculatingtheimportantindexesoftheoptimizedpublictrafficnetwork.Thehierarchicalmethodcannotonlyestablishreasonablepublictrafficnetwork,butalsoimprovetheoperatingefficiencyandservicelevelofpublictrafficnetwork.K
3、eyWords:Urbanpublictrafficnetwork,PSOalgorithmwithmutation,PredictionofODpassengerflow,Hierarchicaloptimization-III-万方数据基于变异粒子群算法的公交线网分层优化研究目录摘要.....................................................................................................................................IA
4、bstract......................................................................................................................................II目录..................................................................................................................................IV1绪
5、论.........................................................................................................................................11.1选题背景和意义..........................................................................................................11.2国内外研究现状.............
6、.............................................................................................21.3主要研究工作内容......................................................................................................42PSO算法的改进分析研究..........................................................
7、..........................................52.1PSO算法概述.............................................................................................................52.2PSO算法的改进.........................................................................................................
8、72.2.1连续PSO算法的改进策略.............................
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