{"title":"支持向量机在商业银行利益相关者资本配置影响中的应用","authors":"Haiqing Hu, Dan Zhang, Duo Huang","doi":"10.1109/ISIP.2008.20","DOIUrl":null,"url":null,"abstract":"In this paper, by using support vector machine (SVM) regression, the simulation model of the influences of stakeholders on capital management in commercial banks is established. The results are tested by utilizing the samples of Chinese joint-stock commercial banks during the period of 1999-2006 and compared with results of PLS regression and BP neural network. The result is gotten that the forecasting precision of SVM is superior to that of PLS regression and BP neural network when the parameters are selected appropriately. Also, it is found that the forecasting precision of various methods in coverage ratio of capital is better than in Meva due to the influence of listing during 1999-2005. The validity of the model is verified.","PeriodicalId":103284,"journal":{"name":"2008 International Symposiums on Information Processing","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Application of SVM on Stakeholders' Influence of Capital Allocation in Commercial Banks\",\"authors\":\"Haiqing Hu, Dan Zhang, Duo Huang\",\"doi\":\"10.1109/ISIP.2008.20\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, by using support vector machine (SVM) regression, the simulation model of the influences of stakeholders on capital management in commercial banks is established. The results are tested by utilizing the samples of Chinese joint-stock commercial banks during the period of 1999-2006 and compared with results of PLS regression and BP neural network. The result is gotten that the forecasting precision of SVM is superior to that of PLS regression and BP neural network when the parameters are selected appropriately. Also, it is found that the forecasting precision of various methods in coverage ratio of capital is better than in Meva due to the influence of listing during 1999-2005. The validity of the model is verified.\",\"PeriodicalId\":103284,\"journal\":{\"name\":\"2008 International Symposiums on Information Processing\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Symposiums on Information Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIP.2008.20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Symposiums on Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIP.2008.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Application of SVM on Stakeholders' Influence of Capital Allocation in Commercial Banks
In this paper, by using support vector machine (SVM) regression, the simulation model of the influences of stakeholders on capital management in commercial banks is established. The results are tested by utilizing the samples of Chinese joint-stock commercial banks during the period of 1999-2006 and compared with results of PLS regression and BP neural network. The result is gotten that the forecasting precision of SVM is superior to that of PLS regression and BP neural network when the parameters are selected appropriately. Also, it is found that the forecasting precision of various methods in coverage ratio of capital is better than in Meva due to the influence of listing during 1999-2005. The validity of the model is verified.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
