PLSME Model of Analyzing Oil-Gas Exploration Risk and Its Applications

详细信息   

• 责任者：Kuang Jianchao (College of Information Management ; Chengdu University of Technology ; Chengdu 610059 ; China) ; Chen Xiaohua
• 刊名：Journal of Chengdu University of Technology
• 出版年：2008
• 卷期：35(1)
• 关键词：油气勘探 ; petroleum exploration
• 页码：p.52-56
• 图表：2 illus., 3 tables, 10 refs.
• 分类号：1003
• issnNo：ISSN1671-9727
• isbnNo：CN51-1634/N

摘要

///A quantitative evaluation of the oil- gas exploration risk has been a difficulty in domestic and foreign researches. This article puts forward the partial least squares (PLS) regression and the maximum entropy (ME) risk analysis model for the first time on the basis of analyzing the disadvantage of the traditional methods and anatomizing the advantage of the partial least squares regression method and the maximum entropy method. The partial least squares regression preferably realizes the integration of multiple linearity regression, principal component analysis and enterprise information maturity. By means of managing the independent variable by the PLS linearity regression, it can not only solve the problem between the variables and eliminate the outliers, but also distinguish every restraining degree from independent variable to dependent variable.