{"title":"利用模糊数据构建转移模型的比较研究","authors":"Esraa Saleh","doi":"10.33899/iqjoss.2018.159246","DOIUrl":null,"url":null,"abstract":"This research consists of using some statistical techniques to study time series for universal prices of wheat as output series and universal product of wheat as input series. By using transfer function on stationary data first , and secondly on stationary fuzzy data , then compare between these two cases to obtain the best transfer function model for data through forecasting criteria to comparing between these two cases .The most suitable model for this data was the transfer function model for stationary fuzzy data because it has minimum value for forecasting criteria","PeriodicalId":351789,"journal":{"name":"IRAQI JOURNAL OF STATISTICAL SCIENCES","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction of the Transfer Model by Using Fuzzy Data: A Comparative Study\",\"authors\":\"Esraa Saleh\",\"doi\":\"10.33899/iqjoss.2018.159246\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research consists of using some statistical techniques to study time series for universal prices of wheat as output series and universal product of wheat as input series. By using transfer function on stationary data first , and secondly on stationary fuzzy data , then compare between these two cases to obtain the best transfer function model for data through forecasting criteria to comparing between these two cases .The most suitable model for this data was the transfer function model for stationary fuzzy data because it has minimum value for forecasting criteria\",\"PeriodicalId\":351789,\"journal\":{\"name\":\"IRAQI JOURNAL OF STATISTICAL SCIENCES\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IRAQI JOURNAL OF STATISTICAL SCIENCES\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33899/iqjoss.2018.159246\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IRAQI JOURNAL OF STATISTICAL SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33899/iqjoss.2018.159246","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Construction of the Transfer Model by Using Fuzzy Data: A Comparative Study
This research consists of using some statistical techniques to study time series for universal prices of wheat as output series and universal product of wheat as input series. By using transfer function on stationary data first , and secondly on stationary fuzzy data , then compare between these two cases to obtain the best transfer function model for data through forecasting criteria to comparing between these two cases .The most suitable model for this data was the transfer function model for stationary fuzzy data because it has minimum value for forecasting criteria