{"title":"新产品开发的神经网络方法与模糊理论","authors":"Xiaoliang Liu, Xiao Liu","doi":"10.1109/IEEC.2010.5533245","DOIUrl":null,"url":null,"abstract":"An ANN-based dynamic FQFD method is proposed in order to solve the dynamic and fuzzy nature of QFD, that solves the problem of the dynamic nature by using neural network method, while the introduction of trapezoidal fuzzy number for its ambiguity. Firstly, a combined method with neural networks and FQFD is established, after learning and training, the method can quickly and effectively deliver customer requirements to the products designers. Finally, a case study demonstrates the effectiveness of the proposed method during the course of new products design.","PeriodicalId":307678,"journal":{"name":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Neural Network Approach and Fuzzy Theory for a New Product Development\",\"authors\":\"Xiaoliang Liu, Xiao Liu\",\"doi\":\"10.1109/IEEC.2010.5533245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An ANN-based dynamic FQFD method is proposed in order to solve the dynamic and fuzzy nature of QFD, that solves the problem of the dynamic nature by using neural network method, while the introduction of trapezoidal fuzzy number for its ambiguity. Firstly, a combined method with neural networks and FQFD is established, after learning and training, the method can quickly and effectively deliver customer requirements to the products designers. Finally, a case study demonstrates the effectiveness of the proposed method during the course of new products design.\",\"PeriodicalId\":307678,\"journal\":{\"name\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Symposium on Information Engineering and Electronic Commerce\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEC.2010.5533245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 2nd International Symposium on Information Engineering and Electronic Commerce","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEC.2010.5533245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Neural Network Approach and Fuzzy Theory for a New Product Development
An ANN-based dynamic FQFD method is proposed in order to solve the dynamic and fuzzy nature of QFD, that solves the problem of the dynamic nature by using neural network method, while the introduction of trapezoidal fuzzy number for its ambiguity. Firstly, a combined method with neural networks and FQFD is established, after learning and training, the method can quickly and effectively deliver customer requirements to the products designers. Finally, a case study demonstrates the effectiveness of the proposed method during the course of new products design.