{"title":"采用反方向平均生成算子构建灰色预测模型","authors":"Baohua Yang, Jinshuai Zhao","doi":"10.1109/GSIS.2017.8077696","DOIUrl":null,"url":null,"abstract":"A grey model with opposite-direction average generating operator is put forward in order to fully extract information concealed in new data. Besides, the relationship between the sample size and the error from the inverse opposite-direction average generating operator is discussed. Compared with traditional grey forecasting model, the results of practical numerical examples have demonstrated that this grey model perform well in forecasting problems with limited data, and can provide reliable and acceptable accuracy for future prediction.","PeriodicalId":425920,"journal":{"name":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using opposite-direction average generating operator to construct grey forecasting model\",\"authors\":\"Baohua Yang, Jinshuai Zhao\",\"doi\":\"10.1109/GSIS.2017.8077696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A grey model with opposite-direction average generating operator is put forward in order to fully extract information concealed in new data. Besides, the relationship between the sample size and the error from the inverse opposite-direction average generating operator is discussed. Compared with traditional grey forecasting model, the results of practical numerical examples have demonstrated that this grey model perform well in forecasting problems with limited data, and can provide reliable and acceptable accuracy for future prediction.\",\"PeriodicalId\":425920,\"journal\":{\"name\":\"2017 International Conference on Grey Systems and Intelligent Services (GSIS)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Grey Systems and Intelligent Services (GSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GSIS.2017.8077696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Grey Systems and Intelligent Services (GSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2017.8077696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using opposite-direction average generating operator to construct grey forecasting model
A grey model with opposite-direction average generating operator is put forward in order to fully extract information concealed in new data. Besides, the relationship between the sample size and the error from the inverse opposite-direction average generating operator is discussed. Compared with traditional grey forecasting model, the results of practical numerical examples have demonstrated that this grey model perform well in forecasting problems with limited data, and can provide reliable and acceptable accuracy for future prediction.