T. Yamasaki, M. Yumoto, T. Ohkawa, N. Komoda, F. Miyasaka
{"title":"建筑空调系统随机定性模型参数自动整定","authors":"T. Yamasaki, M. Yumoto, T. Ohkawa, N. Komoda, F. Miyasaka","doi":"10.1109/INES.1997.632454","DOIUrl":null,"url":null,"abstract":"We have proposed the stochastic qualitative simulation which can derive approximate behavior from a simple qualitative model of a target. In this method, the model must be constructed with numerous stochastic parameters. The parameter tuning process is the most difficult element of model construction. This paper outlines an automatic parameter turning by means of the steepest ascent based method. This method was used in order to generate a model of a real air conditioning system in a building.","PeriodicalId":161975,"journal":{"name":"Proceedings of IEEE International Conference on Intelligent Engineering Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Automatic parameter tuning of stochastic qualitative model of building air conditioning systems\",\"authors\":\"T. Yamasaki, M. Yumoto, T. Ohkawa, N. Komoda, F. Miyasaka\",\"doi\":\"10.1109/INES.1997.632454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have proposed the stochastic qualitative simulation which can derive approximate behavior from a simple qualitative model of a target. In this method, the model must be constructed with numerous stochastic parameters. The parameter tuning process is the most difficult element of model construction. This paper outlines an automatic parameter turning by means of the steepest ascent based method. This method was used in order to generate a model of a real air conditioning system in a building.\",\"PeriodicalId\":161975,\"journal\":{\"name\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE International Conference on Intelligent Engineering Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INES.1997.632454\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE International Conference on Intelligent Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INES.1997.632454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic parameter tuning of stochastic qualitative model of building air conditioning systems
We have proposed the stochastic qualitative simulation which can derive approximate behavior from a simple qualitative model of a target. In this method, the model must be constructed with numerous stochastic parameters. The parameter tuning process is the most difficult element of model construction. This paper outlines an automatic parameter turning by means of the steepest ascent based method. This method was used in order to generate a model of a real air conditioning system in a building.