{"title":"基于支持向量回归的咨询工程公司利润预测","authors":"V. Yepes, E. Pellicer, F. Ferri","doi":"10.1109/ISDA.2009.43","DOIUrl":null,"url":null,"abstract":"This paper introduces Support Vector Machines (SVM) in the particular field of decision support systems for consulting engineering companies and studies the differences and particularities of the corresponding solutions. A detailed analysis has been performed in order to assess the suitability and adaptability of these methods for the particular task taking into account the risk/benefit tradeoff.","PeriodicalId":330324,"journal":{"name":"2009 Ninth International Conference on Intelligent Systems Design and Applications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Profit Forecasting Using Support Vector Regression for Consulting Engineering Firms\",\"authors\":\"V. Yepes, E. Pellicer, F. Ferri\",\"doi\":\"10.1109/ISDA.2009.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces Support Vector Machines (SVM) in the particular field of decision support systems for consulting engineering companies and studies the differences and particularities of the corresponding solutions. A detailed analysis has been performed in order to assess the suitability and adaptability of these methods for the particular task taking into account the risk/benefit tradeoff.\",\"PeriodicalId\":330324,\"journal\":{\"name\":\"2009 Ninth International Conference on Intelligent Systems Design and Applications\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Ninth International Conference on Intelligent Systems Design and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISDA.2009.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Ninth International Conference on Intelligent Systems Design and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISDA.2009.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Profit Forecasting Using Support Vector Regression for Consulting Engineering Firms
This paper introduces Support Vector Machines (SVM) in the particular field of decision support systems for consulting engineering companies and studies the differences and particularities of the corresponding solutions. A detailed analysis has been performed in order to assess the suitability and adaptability of these methods for the particular task taking into account the risk/benefit tradeoff.
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