{"title":"基于T-S模糊自适应扰动粒子群优化和神经网络的优化算法","authors":"Wang Jianfang, L. Weihua","doi":"10.1109/HIS.2009.94","DOIUrl":null,"url":null,"abstract":"To solve fuzzy and non-linear features of mechanical equipment. A new computational intelligence method was proposed by combing based on extended T-S fuzzy model of self-adaptive disturbed PSO and BP neural network algorithm. Firstly, the T-S fuzzy model is modified, and then uses the extended T-S model to adjust the PSO parameter. Secondly, the neural network is trained by the modified PSO algorithm. Finally, a wheel disc model is optimized to check that network model, the test results show that it guarantees the performance of the wheel disc, meanwhile the wheel disc structure is obviously optimized, and the algorithm in the paper is a method of viable structure optimization.","PeriodicalId":414085,"journal":{"name":"2009 Ninth International Conference on Hybrid Intelligent Systems","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimization Algorithm Based on T-S Fuzzy Model of Self-Adaptive Disturbed Particle Swarm Optimization and Neural Network\",\"authors\":\"Wang Jianfang, L. Weihua\",\"doi\":\"10.1109/HIS.2009.94\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve fuzzy and non-linear features of mechanical equipment. A new computational intelligence method was proposed by combing based on extended T-S fuzzy model of self-adaptive disturbed PSO and BP neural network algorithm. Firstly, the T-S fuzzy model is modified, and then uses the extended T-S model to adjust the PSO parameter. Secondly, the neural network is trained by the modified PSO algorithm. Finally, a wheel disc model is optimized to check that network model, the test results show that it guarantees the performance of the wheel disc, meanwhile the wheel disc structure is obviously optimized, and the algorithm in the paper is a method of viable structure optimization.\",\"PeriodicalId\":414085,\"journal\":{\"name\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2009.94\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Ninth International Conference on Hybrid Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2009.94","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization Algorithm Based on T-S Fuzzy Model of Self-Adaptive Disturbed Particle Swarm Optimization and Neural Network
To solve fuzzy and non-linear features of mechanical equipment. A new computational intelligence method was proposed by combing based on extended T-S fuzzy model of self-adaptive disturbed PSO and BP neural network algorithm. Firstly, the T-S fuzzy model is modified, and then uses the extended T-S model to adjust the PSO parameter. Secondly, the neural network is trained by the modified PSO algorithm. Finally, a wheel disc model is optimized to check that network model, the test results show that it guarantees the performance of the wheel disc, meanwhile the wheel disc structure is obviously optimized, and the algorithm in the paper is a method of viable structure optimization.