{"title":"面向服务的生产预测建模","authors":"Jinfa Shi, Hejun Jiao","doi":"10.1109/ICFPEE.2010.13","DOIUrl":null,"url":null,"abstract":"The forecast of production is an important resource for establishing policy. Aimed at the character of the agriculture system, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization from the Service-Oriented Architecture. The result is given that the forecasting model is effective and offers a new method to forecast the grain production.","PeriodicalId":412111,"journal":{"name":"2010 International Conference on Future Power and Energy Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Service-Oriented Modeling of Production Forecasting\",\"authors\":\"Jinfa Shi, Hejun Jiao\",\"doi\":\"10.1109/ICFPEE.2010.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The forecast of production is an important resource for establishing policy. Aimed at the character of the agriculture system, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization from the Service-Oriented Architecture. The result is given that the forecasting model is effective and offers a new method to forecast the grain production.\",\"PeriodicalId\":412111,\"journal\":{\"name\":\"2010 International Conference on Future Power and Energy Engineering\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Future Power and Energy Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICFPEE.2010.13\",\"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 International Conference on Future Power and Energy Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICFPEE.2010.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Service-Oriented Modeling of Production Forecasting
The forecast of production is an important resource for establishing policy. Aimed at the character of the agriculture system, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization from the Service-Oriented Architecture. The result is given that the forecasting model is effective and offers a new method to forecast the grain production.
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