{"title":"基于改进遗传神经网络的图书采购模型分析","authors":"Runhua Wang, Yi Tang, Guoquan Liu, Lei Li","doi":"10.1109/ICCI-CC.2012.6311188","DOIUrl":null,"url":null,"abstract":"A modeling method based on genetic neural network used for book purchasing is put forward on account of lacking of a set of scientific and uniform purchasing mode and model in current book purchasing process. This method improves standard genetic algorithm first, and then uses the improved standard genetic algorithm as a method of feed forward neural network training and threshold value of feed forward neural network weight adjustment, after that, explores potential relationship between various properties of book and whether it is purchased or not through optimized neural network, thereby to realize the forecast classification whether the book should be purchased or not. Simulation experiment shows good forecast performance and generalization ability of the book purchasing model, thus it is worth for promotion.","PeriodicalId":427778,"journal":{"name":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","volume":"124 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of book purchasing model based on improved genetic neural network\",\"authors\":\"Runhua Wang, Yi Tang, Guoquan Liu, Lei Li\",\"doi\":\"10.1109/ICCI-CC.2012.6311188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A modeling method based on genetic neural network used for book purchasing is put forward on account of lacking of a set of scientific and uniform purchasing mode and model in current book purchasing process. This method improves standard genetic algorithm first, and then uses the improved standard genetic algorithm as a method of feed forward neural network training and threshold value of feed forward neural network weight adjustment, after that, explores potential relationship between various properties of book and whether it is purchased or not through optimized neural network, thereby to realize the forecast classification whether the book should be purchased or not. Simulation experiment shows good forecast performance and generalization ability of the book purchasing model, thus it is worth for promotion.\",\"PeriodicalId\":427778,\"journal\":{\"name\":\"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing\",\"volume\":\"124 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCI-CC.2012.6311188\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCI-CC.2012.6311188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of book purchasing model based on improved genetic neural network
A modeling method based on genetic neural network used for book purchasing is put forward on account of lacking of a set of scientific and uniform purchasing mode and model in current book purchasing process. This method improves standard genetic algorithm first, and then uses the improved standard genetic algorithm as a method of feed forward neural network training and threshold value of feed forward neural network weight adjustment, after that, explores potential relationship between various properties of book and whether it is purchased or not through optimized neural network, thereby to realize the forecast classification whether the book should be purchased or not. Simulation experiment shows good forecast performance and generalization ability of the book purchasing model, thus it is worth for promotion.