{"title":"最优SCGM(1,1)-Markov模型在节水指标模拟与预测中的应用","authors":"Fei Su, Z. Dong, Bagen Chaolun","doi":"10.1109/ICIC.2010.204","DOIUrl":null,"url":null,"abstract":"Most indexes of water-saving are lack of observed data since water-saving society building as a newly complex work in China. The indexes have both the characteristics of short-term trend and stochastic variety. So it is an important work to predict them reasonably and timely. Considering all the characteristics uniformly the system cloud grey model and Markov theory are combined to form SCGM(1,1)-Markov model, and the parameters are optimized at the same time. The application results show the optimal model has higher precision on simulation than commonly used methods by 24 indexes, and the model has robust prediction ability for those indexes. The most possible value ranges of the 24 indexes are predicted by the model for 2010 also. It provides the reference to decision-making on water use planning for the management organization in the study area.","PeriodicalId":176212,"journal":{"name":"2010 Third International Conference on Information and Computing","volume":"149 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Application of Optimal SCGM(1,1)-Markov Model for Simulation and Prediction on Indexes of Water-saving\",\"authors\":\"Fei Su, Z. Dong, Bagen Chaolun\",\"doi\":\"10.1109/ICIC.2010.204\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most indexes of water-saving are lack of observed data since water-saving society building as a newly complex work in China. The indexes have both the characteristics of short-term trend and stochastic variety. So it is an important work to predict them reasonably and timely. Considering all the characteristics uniformly the system cloud grey model and Markov theory are combined to form SCGM(1,1)-Markov model, and the parameters are optimized at the same time. The application results show the optimal model has higher precision on simulation than commonly used methods by 24 indexes, and the model has robust prediction ability for those indexes. The most possible value ranges of the 24 indexes are predicted by the model for 2010 also. It provides the reference to decision-making on water use planning for the management organization in the study area.\",\"PeriodicalId\":176212,\"journal\":{\"name\":\"2010 Third International Conference on Information and Computing\",\"volume\":\"149 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Conference on Information and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIC.2010.204\",\"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 Third International Conference on Information and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIC.2010.204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Application of Optimal SCGM(1,1)-Markov Model for Simulation and Prediction on Indexes of Water-saving
Most indexes of water-saving are lack of observed data since water-saving society building as a newly complex work in China. The indexes have both the characteristics of short-term trend and stochastic variety. So it is an important work to predict them reasonably and timely. Considering all the characteristics uniformly the system cloud grey model and Markov theory are combined to form SCGM(1,1)-Markov model, and the parameters are optimized at the same time. The application results show the optimal model has higher precision on simulation than commonly used methods by 24 indexes, and the model has robust prediction ability for those indexes. The most possible value ranges of the 24 indexes are predicted by the model for 2010 also. It provides the reference to decision-making on water use planning for the management organization in the study area.