{"title":"基于可拓聚类模型的公交交通量预测","authors":"Wenjuan Wang, Yongquan Yu, Shoujian Lan","doi":"10.1109/ICACTE.2010.5579051","DOIUrl":null,"url":null,"abstract":"This paper analyze the influential factors of bus traffic volume. Use the concept of matter-element and correlation function to establish prediction model, the prediction results can be obtained by means of cluster analysis. Through analyzing and calculating the historical data of Guangzhou City, the results show that the model in the bus traffic volume is valid.","PeriodicalId":255806,"journal":{"name":"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of bus traffic volume based on extension cluster model\",\"authors\":\"Wenjuan Wang, Yongquan Yu, Shoujian Lan\",\"doi\":\"10.1109/ICACTE.2010.5579051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper analyze the influential factors of bus traffic volume. Use the concept of matter-element and correlation function to establish prediction model, the prediction results can be obtained by means of cluster analysis. Through analyzing and calculating the historical data of Guangzhou City, the results show that the model in the bus traffic volume is valid.\",\"PeriodicalId\":255806,\"journal\":{\"name\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACTE.2010.5579051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACTE.2010.5579051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of bus traffic volume based on extension cluster model
This paper analyze the influential factors of bus traffic volume. Use the concept of matter-element and correlation function to establish prediction model, the prediction results can be obtained by means of cluster analysis. Through analyzing and calculating the historical data of Guangzhou City, the results show that the model in the bus traffic volume is valid.
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