{"title":"反向传播神经网络在星座预测中的应用","authors":"Usha Sharma, S. Karmakar, Navita Shrivastava.","doi":"10.5120/IJAIS2016451575","DOIUrl":null,"url":null,"abstract":"In this study a back-propagation neural network model is designed and its parameters are optimized for prediction of horoscope to identify a person type. Person type is a dynamic system based on the planet system. It is found that the backpropagation neural network is capable to predict the person type by learning planet dataset. The model is trained up to model error (i.e., mean square error) 1.2864E-04 and performs excellent during training and testing process.","PeriodicalId":92376,"journal":{"name":"International journal of applied information systems","volume":"29 1","pages":"8-15"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Back-Propagation Neural Network in Horoscope Prediction\",\"authors\":\"Usha Sharma, S. Karmakar, Navita Shrivastava.\",\"doi\":\"10.5120/IJAIS2016451575\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study a back-propagation neural network model is designed and its parameters are optimized for prediction of horoscope to identify a person type. Person type is a dynamic system based on the planet system. It is found that the backpropagation neural network is capable to predict the person type by learning planet dataset. The model is trained up to model error (i.e., mean square error) 1.2864E-04 and performs excellent during training and testing process.\",\"PeriodicalId\":92376,\"journal\":{\"name\":\"International journal of applied information systems\",\"volume\":\"29 1\",\"pages\":\"8-15\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of applied information systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5120/IJAIS2016451575\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied information systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5120/IJAIS2016451575","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Back-Propagation Neural Network in Horoscope Prediction
In this study a back-propagation neural network model is designed and its parameters are optimized for prediction of horoscope to identify a person type. Person type is a dynamic system based on the planet system. It is found that the backpropagation neural network is capable to predict the person type by learning planet dataset. The model is trained up to model error (i.e., mean square error) 1.2864E-04 and performs excellent during training and testing process.
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