{"title":"基于神经网络的建筑陶瓷缺陷分析","authors":"Yang Li-hua","doi":"10.1109/ICSSEM.2011.6081197","DOIUrl":null,"url":null,"abstract":"This paper uses the BP neural network to analyze the defects of building ceramics, and researches the relationship between building ceramic defects and material. And the results show that the BP neural network method is feasible for being used to analyzing the relationship between the Building ceramics defects and material, at the same time, the paper provides a new method for ceramic defects analysis.","PeriodicalId":406311,"journal":{"name":"2011 International Conference on System science, Engineering design and Manufacturing informatization","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of building ceramic defects based on neural network\",\"authors\":\"Yang Li-hua\",\"doi\":\"10.1109/ICSSEM.2011.6081197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper uses the BP neural network to analyze the defects of building ceramics, and researches the relationship between building ceramic defects and material. And the results show that the BP neural network method is feasible for being used to analyzing the relationship between the Building ceramics defects and material, at the same time, the paper provides a new method for ceramic defects analysis.\",\"PeriodicalId\":406311,\"journal\":{\"name\":\"2011 International Conference on System science, Engineering design and Manufacturing informatization\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on System science, Engineering design and Manufacturing informatization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSEM.2011.6081197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on System science, Engineering design and Manufacturing informatization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSEM.2011.6081197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of building ceramic defects based on neural network
This paper uses the BP neural network to analyze the defects of building ceramics, and researches the relationship between building ceramic defects and material. And the results show that the BP neural network method is feasible for being used to analyzing the relationship between the Building ceramics defects and material, at the same time, the paper provides a new method for ceramic defects analysis.
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