{"title":"一种选择径向基函数网络中心的新算法","authors":"Hong-rui Wang, Hong-bin Wang, Li-xin Wei, Ying Li","doi":"10.1109/ICMLC.2002.1175350","DOIUrl":null,"url":null,"abstract":"The selecting of the radial basis function center is a key factor that influences the performance of networks. In this paper we first introduce briefly the fuzzy c-mean algorithm and k-nearest-neighbor algorithm as to the selection of the radial basis function center, and then we present a /spl delta/-nearest-neighbor cluster algorithm which combines the k-nearest-neighbor algorithm with fuzzy c-mean algorithm. Finally, we demonstrate the performance results for dynamic system identification via simulations.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"29 1","pages":"1801-1804 vol.4"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A new algorithm of selecting the radial basis function networks center\",\"authors\":\"Hong-rui Wang, Hong-bin Wang, Li-xin Wei, Ying Li\",\"doi\":\"10.1109/ICMLC.2002.1175350\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The selecting of the radial basis function center is a key factor that influences the performance of networks. In this paper we first introduce briefly the fuzzy c-mean algorithm and k-nearest-neighbor algorithm as to the selection of the radial basis function center, and then we present a /spl delta/-nearest-neighbor cluster algorithm which combines the k-nearest-neighbor algorithm with fuzzy c-mean algorithm. Finally, we demonstrate the performance results for dynamic system identification via simulations.\",\"PeriodicalId\":90702,\"journal\":{\"name\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"volume\":\"29 1\",\"pages\":\"1801-1804 vol.4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2002.1175350\",\"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. International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2002.1175350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new algorithm of selecting the radial basis function networks center
The selecting of the radial basis function center is a key factor that influences the performance of networks. In this paper we first introduce briefly the fuzzy c-mean algorithm and k-nearest-neighbor algorithm as to the selection of the radial basis function center, and then we present a /spl delta/-nearest-neighbor cluster algorithm which combines the k-nearest-neighbor algorithm with fuzzy c-mean algorithm. Finally, we demonstrate the performance results for dynamic system identification via simulations.