G. Lambert-Torres, L. E. Borges da Silva, B. Valiquette, H. Greiss, D. Mukhedkar
{"title":"基于模糊知识的客车负荷预测系统","authors":"G. Lambert-Torres, L. E. Borges da Silva, B. Valiquette, H. Greiss, D. Mukhedkar","doi":"10.1109/FUZZY.1992.258650","DOIUrl":null,"url":null,"abstract":"The authors describe an alternative approach to short-term load forecasting. The approach merges traditional mathematical techniques and fuzzy concepts in a knowledge base. The rules of this knowledge base are devised using the historical data of the bus and are represented by fuzzy conditional statements. An example using real data from an actual power system is presented.<<ETX>>","PeriodicalId":222263,"journal":{"name":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"A fuzzy knowledge-based system for bus load forecasting\",\"authors\":\"G. Lambert-Torres, L. E. Borges da Silva, B. Valiquette, H. Greiss, D. Mukhedkar\",\"doi\":\"10.1109/FUZZY.1992.258650\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors describe an alternative approach to short-term load forecasting. The approach merges traditional mathematical techniques and fuzzy concepts in a knowledge base. The rules of this knowledge base are devised using the historical data of the bus and are represented by fuzzy conditional statements. An example using real data from an actual power system is presented.<<ETX>>\",\"PeriodicalId\":222263,\"journal\":{\"name\":\"[1992 Proceedings] IEEE International Conference on Fuzzy Systems\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1992 Proceedings] IEEE International Conference on Fuzzy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZY.1992.258650\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992 Proceedings] IEEE International Conference on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.1992.258650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A fuzzy knowledge-based system for bus load forecasting
The authors describe an alternative approach to short-term load forecasting. The approach merges traditional mathematical techniques and fuzzy concepts in a knowledge base. The rules of this knowledge base are devised using the historical data of the bus and are represented by fuzzy conditional statements. An example using real data from an actual power system is presented.<>