{"title":"非参数回归算法在短期交通流预测中的应用","authors":"Wang Xinying, J. Zhicai, Liu Miao, Sun Yuan","doi":"10.1109/ETCS.2009.707","DOIUrl":null,"url":null,"abstract":"Short-term traffic flow forecast is an important topic in the research field of intelligent transportation systems. The article analyses the preliminary results in the short-term traffic flow forecast, takes full advantage of the characteristics of K-neatest neighbor (KNN) classifiers, and builds a model based on nonparametric regressive algorithm.The historical and metrical data is classified by KNN,and the state vector is constructed by utilizing the output of KNN classifier. Traffic flow forecasting for the next period is entirely based on the state vectors.The experimental results show that the model was verified more accurate.","PeriodicalId":422513,"journal":{"name":"2009 First International Workshop on Education Technology and Computer Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"The Application of Nonparametric Regressive Algorithm for Short-Term Traffic Flow Forecast\",\"authors\":\"Wang Xinying, J. Zhicai, Liu Miao, Sun Yuan\",\"doi\":\"10.1109/ETCS.2009.707\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Short-term traffic flow forecast is an important topic in the research field of intelligent transportation systems. The article analyses the preliminary results in the short-term traffic flow forecast, takes full advantage of the characteristics of K-neatest neighbor (KNN) classifiers, and builds a model based on nonparametric regressive algorithm.The historical and metrical data is classified by KNN,and the state vector is constructed by utilizing the output of KNN classifier. Traffic flow forecasting for the next period is entirely based on the state vectors.The experimental results show that the model was verified more accurate.\",\"PeriodicalId\":422513,\"journal\":{\"name\":\"2009 First International Workshop on Education Technology and Computer Science\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 First International Workshop on Education Technology and Computer Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ETCS.2009.707\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 First International Workshop on Education Technology and Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCS.2009.707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Application of Nonparametric Regressive Algorithm for Short-Term Traffic Flow Forecast
Short-term traffic flow forecast is an important topic in the research field of intelligent transportation systems. The article analyses the preliminary results in the short-term traffic flow forecast, takes full advantage of the characteristics of K-neatest neighbor (KNN) classifiers, and builds a model based on nonparametric regressive algorithm.The historical and metrical data is classified by KNN,and the state vector is constructed by utilizing the output of KNN classifier. Traffic flow forecasting for the next period is entirely based on the state vectors.The experimental results show that the model was verified more accurate.