{"title":"BP神经网络和灰色神经网络在大学毕业生就业预测中的应用","authors":"Jin Zheng","doi":"10.1109/ICACTE.2010.5579436","DOIUrl":null,"url":null,"abstract":"With the help of neural network theory and the employment data of six majors' graduates (vehicle engineering, finance, traffic engineering, computer, applied Chemistry, law) in one university from 2002 to 2009, we study the application of these theories and models in the area of employment forecasting. By comparing the predicted results and actual ones, we verify and analyze the accuracy of these two models in forecasting, and further predict the employment situation of graduates of this university in 2010.","PeriodicalId":255806,"journal":{"name":"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The application of BP neural network and gray neural network in university graduates' employment forecasting\",\"authors\":\"Jin Zheng\",\"doi\":\"10.1109/ICACTE.2010.5579436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the help of neural network theory and the employment data of six majors' graduates (vehicle engineering, finance, traffic engineering, computer, applied Chemistry, law) in one university from 2002 to 2009, we study the application of these theories and models in the area of employment forecasting. By comparing the predicted results and actual ones, we verify and analyze the accuracy of these two models in forecasting, and further predict the employment situation of graduates of this university in 2010.\",\"PeriodicalId\":255806,\"journal\":{\"name\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACTE.2010.5579436\",\"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 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACTE.2010.5579436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of BP neural network and gray neural network in university graduates' employment forecasting
With the help of neural network theory and the employment data of six majors' graduates (vehicle engineering, finance, traffic engineering, computer, applied Chemistry, law) in one university from 2002 to 2009, we study the application of these theories and models in the area of employment forecasting. By comparing the predicted results and actual ones, we verify and analyze the accuracy of these two models in forecasting, and further predict the employment situation of graduates of this university in 2010.