{"title":"基于虚拟驾驶员的多元离散灰色模型","authors":"Ke Zhang","doi":"10.1108/GS-09-2015-0051","DOIUrl":null,"url":null,"abstract":"A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are proposed. At last, the per capita income forecasting of rural residents in Henan province of China is solved with the proposed model. The results are compared with other grey forecasting models, and prove that proposed model has not only high accuracy, but also clear physical meaning.","PeriodicalId":246110,"journal":{"name":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Multivariate Discrete Grey Model base on Dummy Drivers\",\"authors\":\"Ke Zhang\",\"doi\":\"10.1108/GS-09-2015-0051\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are proposed. At last, the per capita income forecasting of rural residents in Henan province of China is solved with the proposed model. The results are compared with other grey forecasting models, and prove that proposed model has not only high accuracy, but also clear physical meaning.\",\"PeriodicalId\":246110,\"journal\":{\"name\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/GS-09-2015-0051\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Grey Systems and Intelligent Services (GSIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/GS-09-2015-0051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multivariate Discrete Grey Model base on Dummy Drivers
A multivariate discrete grey forecasting model is proposed to solve the problem that the qualitative relative factors can't be employed in traditional models. Firstly, a new model is constructed though introducing dummy drivers. Then, the parameters estimation method and recursive function of the model are discussed. Furthermore, dummy driver setting, pre and posttest methods of dummy drivers are proposed. At last, the per capita income forecasting of rural residents in Henan province of China is solved with the proposed model. The results are compared with other grey forecasting models, and prove that proposed model has not only high accuracy, but also clear physical meaning.