{"title":"Application of a fuzzy knowledge base on bus operations under uncertainty","authors":"Jao-Hong Cheng, Yu-Hern Chang","doi":"10.1109/FUZZY.1999.790100","DOIUrl":null,"url":null,"abstract":"In the day-to-day operation of a bus system, vehicle and crew schedules are often changed due to uncertain or unexpected conditions. To better address the practical bus operations problem, this research constructs a knowledge-based expertise for handling unexpected variations in demand. Significant results achieved by this research include the following: a commonly used linguistic descriptors in bus operations for various uncertain demand conditions are collected from experts. Individual experts' knowledge and judgement are properly adjusted to obtain membership functions for forming the fuzzification interface. A twenty-five generic fuzzy logic rules constructed can handle both single and multiple uncertain conditions. These rules have been extensively tested on real bus systems which demonstrate their relevance and applicability to any bus system.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.1999.790100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In the day-to-day operation of a bus system, vehicle and crew schedules are often changed due to uncertain or unexpected conditions. To better address the practical bus operations problem, this research constructs a knowledge-based expertise for handling unexpected variations in demand. Significant results achieved by this research include the following: a commonly used linguistic descriptors in bus operations for various uncertain demand conditions are collected from experts. Individual experts' knowledge and judgement are properly adjusted to obtain membership functions for forming the fuzzification interface. A twenty-five generic fuzzy logic rules constructed can handle both single and multiple uncertain conditions. These rules have been extensively tested on real bus systems which demonstrate their relevance and applicability to any bus system.