Tanuja Shanmukhappa, I. W. Ho, C. Tse, Xingtang Wu, Hai-rong Dong
{"title":"多层公共交通网络分析","authors":"Tanuja Shanmukhappa, I. W. Ho, C. Tse, Xingtang Wu, Hai-rong Dong","doi":"10.1109/ISCAS.2018.8351818","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel method called supernode graph structure representation to model the public transport network structure of the London city. Supernode is a set of geographically closely associated nodes. Using the supernode graph structure, the bus transport and the metro transport network structures are analyzed by treating them as independent mono-layer or multi-layer network structures. A method of spatial amalgamation is proposed to integrate the two transport layers. A set of most influential nodes in the network is identified by assigning node weight to each node with respect to both mono-layer and multi-layer analysis. The behavior of these influential nodes is better characterized by categorizing them as either emitter, absorber or neutral zones.","PeriodicalId":6569,"journal":{"name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","volume":"3 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Multi-layer Public Transport Network Analysis\",\"authors\":\"Tanuja Shanmukhappa, I. W. Ho, C. Tse, Xingtang Wu, Hai-rong Dong\",\"doi\":\"10.1109/ISCAS.2018.8351818\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a novel method called supernode graph structure representation to model the public transport network structure of the London city. Supernode is a set of geographically closely associated nodes. Using the supernode graph structure, the bus transport and the metro transport network structures are analyzed by treating them as independent mono-layer or multi-layer network structures. A method of spatial amalgamation is proposed to integrate the two transport layers. A set of most influential nodes in the network is identified by assigning node weight to each node with respect to both mono-layer and multi-layer analysis. The behavior of these influential nodes is better characterized by categorizing them as either emitter, absorber or neutral zones.\",\"PeriodicalId\":6569,\"journal\":{\"name\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"volume\":\"3 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Symposium on Circuits and Systems (ISCAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCAS.2018.8351818\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCAS.2018.8351818","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a novel method called supernode graph structure representation to model the public transport network structure of the London city. Supernode is a set of geographically closely associated nodes. Using the supernode graph structure, the bus transport and the metro transport network structures are analyzed by treating them as independent mono-layer or multi-layer network structures. A method of spatial amalgamation is proposed to integrate the two transport layers. A set of most influential nodes in the network is identified by assigning node weight to each node with respect to both mono-layer and multi-layer analysis. The behavior of these influential nodes is better characterized by categorizing them as either emitter, absorber or neutral zones.