{"title":"基于模糊逻辑的出发地矩阵估计","authors":"Asma Sbai, Fattehallah Ghadi","doi":"10.1109/ICOA.2018.8370568","DOIUrl":null,"url":null,"abstract":"Trip distribution is the second sub model of the four step model of transportation planning process. It aims to estimate the number of trips between a pair of zones. Previous studies have investigated different techniques to estimate demand of citizens, some relaying on static approach and other using dynamic approach. In this paper we will consider the use of fuzzy logic technique by means of productions and attractions trips and distance between zones. We will also compare it with the traditional gravity model implemented in different modeling software.","PeriodicalId":433166,"journal":{"name":"2018 4th International Conference on Optimization and Applications (ICOA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimation of origin destination matrix using fuzzy logic\",\"authors\":\"Asma Sbai, Fattehallah Ghadi\",\"doi\":\"10.1109/ICOA.2018.8370568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Trip distribution is the second sub model of the four step model of transportation planning process. It aims to estimate the number of trips between a pair of zones. Previous studies have investigated different techniques to estimate demand of citizens, some relaying on static approach and other using dynamic approach. In this paper we will consider the use of fuzzy logic technique by means of productions and attractions trips and distance between zones. We will also compare it with the traditional gravity model implemented in different modeling software.\",\"PeriodicalId\":433166,\"journal\":{\"name\":\"2018 4th International Conference on Optimization and Applications (ICOA)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 4th International Conference on Optimization and Applications (ICOA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOA.2018.8370568\",\"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 4th International Conference on Optimization and Applications (ICOA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOA.2018.8370568","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of origin destination matrix using fuzzy logic
Trip distribution is the second sub model of the four step model of transportation planning process. It aims to estimate the number of trips between a pair of zones. Previous studies have investigated different techniques to estimate demand of citizens, some relaying on static approach and other using dynamic approach. In this paper we will consider the use of fuzzy logic technique by means of productions and attractions trips and distance between zones. We will also compare it with the traditional gravity model implemented in different modeling software.
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