{"title":"基于多层残差修正的不等区间GM(1,1)预测模型的构建及应用","authors":"Ling Kegang","doi":"10.1109/GSIS.2009.5408269","DOIUrl":null,"url":null,"abstract":"Prediction for slope displacement can prevent the occurrence of slope disasters effectively. Original grey GM(1,1) model is usually used in simulation and prediction of equidistant monitoring data sequence, but the actual situation is the monitoring data which obtained appear unequal interval phenomenon. So, unequal interval grey GM(1,1) model is established after analyzing the establishing principal of original equal interval GM(1,1) model, and the method for calculating the grey parameter is discussed. At last, the improved model is applied for analyzing the B3 monitoring data of a slope of the YU-QIAN highway. By comparing the improved method for grey parameter calculation with the conventional method, it is proved that the modified GM(1,1) model has high accuracy and the prediction results agrees well with the actual behavior of the slope.","PeriodicalId":294363,"journal":{"name":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Construction and application of unequal interval GM (1,1) prediction model based on multilevel residual amendment\",\"authors\":\"Ling Kegang\",\"doi\":\"10.1109/GSIS.2009.5408269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prediction for slope displacement can prevent the occurrence of slope disasters effectively. Original grey GM(1,1) model is usually used in simulation and prediction of equidistant monitoring data sequence, but the actual situation is the monitoring data which obtained appear unequal interval phenomenon. So, unequal interval grey GM(1,1) model is established after analyzing the establishing principal of original equal interval GM(1,1) model, and the method for calculating the grey parameter is discussed. At last, the improved model is applied for analyzing the B3 monitoring data of a slope of the YU-QIAN highway. By comparing the improved method for grey parameter calculation with the conventional method, it is proved that the modified GM(1,1) model has high accuracy and the prediction results agrees well with the actual behavior of the slope.\",\"PeriodicalId\":294363,\"journal\":{\"name\":\"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GSIS.2009.5408269\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GSIS.2009.5408269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Construction and application of unequal interval GM (1,1) prediction model based on multilevel residual amendment
Prediction for slope displacement can prevent the occurrence of slope disasters effectively. Original grey GM(1,1) model is usually used in simulation and prediction of equidistant monitoring data sequence, but the actual situation is the monitoring data which obtained appear unequal interval phenomenon. So, unequal interval grey GM(1,1) model is established after analyzing the establishing principal of original equal interval GM(1,1) model, and the method for calculating the grey parameter is discussed. At last, the improved model is applied for analyzing the B3 monitoring data of a slope of the YU-QIAN highway. By comparing the improved method for grey parameter calculation with the conventional method, it is proved that the modified GM(1,1) model has high accuracy and the prediction results agrees well with the actual behavior of the slope.