{"title":"优化背景值GM(1,1)模型预测油气生产成本","authors":"Yue Zhao, Songzheng Zhao","doi":"10.1109/FSKD.2012.6234255","DOIUrl":null,"url":null,"abstract":"Oil-gas production cost, as an important indicator which reflects the economic benefit of oilfield enterprise, plays a significant role to analyze the economic feasibility. Following taking the characteristics of original GM(1,1) model into account, determinants concerning fitting precision and prediction precision that belong to the original GM(1,1) are identified. Optimization background value GM(1,1) model is proposed to predict oil-gas production cost. Through comparing with the original GM(1,1) model in terms of fitting precision and prediction precision, the results exhibit that the optimization background value GM(1,1) model has the automated optimization background value capability and may ensure the excellent adaptability.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization background value GM(1, 1) model for predicting oil-gas production cost\",\"authors\":\"Yue Zhao, Songzheng Zhao\",\"doi\":\"10.1109/FSKD.2012.6234255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Oil-gas production cost, as an important indicator which reflects the economic benefit of oilfield enterprise, plays a significant role to analyze the economic feasibility. Following taking the characteristics of original GM(1,1) model into account, determinants concerning fitting precision and prediction precision that belong to the original GM(1,1) are identified. Optimization background value GM(1,1) model is proposed to predict oil-gas production cost. Through comparing with the original GM(1,1) model in terms of fitting precision and prediction precision, the results exhibit that the optimization background value GM(1,1) model has the automated optimization background value capability and may ensure the excellent adaptability.\",\"PeriodicalId\":337941,\"journal\":{\"name\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Fuzzy Systems and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2012.6234255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Fuzzy Systems and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2012.6234255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization background value GM(1, 1) model for predicting oil-gas production cost
Oil-gas production cost, as an important indicator which reflects the economic benefit of oilfield enterprise, plays a significant role to analyze the economic feasibility. Following taking the characteristics of original GM(1,1) model into account, determinants concerning fitting precision and prediction precision that belong to the original GM(1,1) are identified. Optimization background value GM(1,1) model is proposed to predict oil-gas production cost. Through comparing with the original GM(1,1) model in terms of fitting precision and prediction precision, the results exhibit that the optimization background value GM(1,1) model has the automated optimization background value capability and may ensure the excellent adaptability.