{"title":"基于偏最小二乘回归的神经网络与投影寻踪耦合模型在水资源承载力预测中的应用","authors":"Xiao-Yong Zhao","doi":"10.1109/ISCID.2012.261","DOIUrl":null,"url":null,"abstract":"The method of partial least-squares regression can effectively deal with the problems of multicollinearity among independent variables\", \"but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with neural network and projection pursuit is an ideal tool to deal with the problem of nonlinearity, and it is very steady, but can not ideally solve the problems of multicollinearity among independent variables. The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression for forecast water resources carrying capacity. the results of forecasting indicate that the combination is superior to either of them, the model was found to be able to give satisfactory effect.","PeriodicalId":246432,"journal":{"name":"2012 Fifth International Symposium on Computational Intelligence and Design","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Application of Coupling Model with Neural Network and Projection Pursuit Based on Partial Least-Squares Regression to Water Resources Carrying Capacity Forecasting\",\"authors\":\"Xiao-Yong Zhao\",\"doi\":\"10.1109/ISCID.2012.261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The method of partial least-squares regression can effectively deal with the problems of multicollinearity among independent variables\\\", \\\"but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with neural network and projection pursuit is an ideal tool to deal with the problem of nonlinearity, and it is very steady, but can not ideally solve the problems of multicollinearity among independent variables. The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression for forecast water resources carrying capacity. the results of forecasting indicate that the combination is superior to either of them, the model was found to be able to give satisfactory effect.\",\"PeriodicalId\":246432,\"journal\":{\"name\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2012.261\",\"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 Fifth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2012.261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Coupling Model with Neural Network and Projection Pursuit Based on Partial Least-Squares Regression to Water Resources Carrying Capacity Forecasting
The method of partial least-squares regression can effectively deal with the problems of multicollinearity among independent variables", "but can not ideally solve the complicated problems of nonlinearity between dependent variables and independent variables. The method of coupling model with neural network and projection pursuit is an ideal tool to deal with the problem of nonlinearity, and it is very steady, but can not ideally solve the problems of multicollinearity among independent variables. The paper combines the two methods to establish the method of coupling model with neural network and projection pursuit based on partial least-squares regression for forecast water resources carrying capacity. the results of forecasting indicate that the combination is superior to either of them, the model was found to be able to give satisfactory effect.