{"title":"基于模糊逻辑和动态染色体遗传算法的植物标识符训练集生成","authors":"N. Nahapetian, M. Analoui, M. Jahed-Motlagh","doi":"10.1109/CICA.2009.4982782","DOIUrl":null,"url":null,"abstract":"Training set is one of the main critical sections in Neural Network, generating of it with prior knowledge can be extremely efficient. In this paper we have tried to explore the potential of using previously generated training set (not randomly) for the training of Dynamic Neural Network. The neural network was used as the core of identifier which tries to identify the internal behavior of structure-unknown non-linear time variant dynamic system.","PeriodicalId":383751,"journal":{"name":"2009 IEEE Symposium on Computational Intelligence in Control and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Training set generation using fuzzy logic and dynamic chromosome based Genetic Algorithms for plant identifiers\",\"authors\":\"N. Nahapetian, M. Analoui, M. Jahed-Motlagh\",\"doi\":\"10.1109/CICA.2009.4982782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Training set is one of the main critical sections in Neural Network, generating of it with prior knowledge can be extremely efficient. In this paper we have tried to explore the potential of using previously generated training set (not randomly) for the training of Dynamic Neural Network. The neural network was used as the core of identifier which tries to identify the internal behavior of structure-unknown non-linear time variant dynamic system.\",\"PeriodicalId\":383751,\"journal\":{\"name\":\"2009 IEEE Symposium on Computational Intelligence in Control and Automation\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Symposium on Computational Intelligence in Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CICA.2009.4982782\",\"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 IEEE Symposium on Computational Intelligence in Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CICA.2009.4982782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Training set generation using fuzzy logic and dynamic chromosome based Genetic Algorithms for plant identifiers
Training set is one of the main critical sections in Neural Network, generating of it with prior knowledge can be extremely efficient. In this paper we have tried to explore the potential of using previously generated training set (not randomly) for the training of Dynamic Neural Network. The neural network was used as the core of identifier which tries to identify the internal behavior of structure-unknown non-linear time variant dynamic system.
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