{"title":"基于遗传神经网络的激光淬火专家系统研究","authors":"Qingwu Fan, Pu Wang, Lianbao Zhang, Jun Li","doi":"10.1109/WCICA.2006.1713523","DOIUrl":null,"url":null,"abstract":"Traditional method about designing blue print in course of surface laser quenching was studied. Expert system of laser quenching based on genetic-neural network was presented. Knowledge acquisition, construction of knowledge base and design of inference engine were introduced in detail. The trial running results show that this research raised an advanced and reasonable path for performance prediction and optimization design of laser quenching","PeriodicalId":375135,"journal":{"name":"2006 6th World Congress on Intelligent Control and Automation","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Research of Expert System of Laser Quenching Based on Genetic-Neural Network\",\"authors\":\"Qingwu Fan, Pu Wang, Lianbao Zhang, Jun Li\",\"doi\":\"10.1109/WCICA.2006.1713523\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional method about designing blue print in course of surface laser quenching was studied. Expert system of laser quenching based on genetic-neural network was presented. Knowledge acquisition, construction of knowledge base and design of inference engine were introduced in detail. The trial running results show that this research raised an advanced and reasonable path for performance prediction and optimization design of laser quenching\",\"PeriodicalId\":375135,\"journal\":{\"name\":\"2006 6th World Congress on Intelligent Control and Automation\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 6th World Congress on Intelligent Control and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCICA.2006.1713523\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 6th World Congress on Intelligent Control and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCICA.2006.1713523","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Research of Expert System of Laser Quenching Based on Genetic-Neural Network
Traditional method about designing blue print in course of surface laser quenching was studied. Expert system of laser quenching based on genetic-neural network was presented. Knowledge acquisition, construction of knowledge base and design of inference engine were introduced in detail. The trial running results show that this research raised an advanced and reasonable path for performance prediction and optimization design of laser quenching
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