高校地质学报2017，Vol.23Issue(2)：366-372,7.DOI:10.16108/j.issn1006-7493.2016198
基于主成分分析的多项Logistic回归模型的突水水源判别研究
Study on Water Source Discrimination Based on Multinomial Logistic Regression Model Using Principal Component Analysis
摘要
Abstract
Mine water disaster is one of the most common geological disasters in mine production process.Quickly and effectively determine the source of water inrush is a key to the prevention of mine water damage.The data of 59 water samples were selected in Yuaner coal mine.The data of water sample mainly include constant ion content.The content of constant ions was treated by principal component analysis.The principal component scores were used as independent variables.The water source category is used as a dependent variable.Multinomial logistic regression models were established by using these.The regression model was used to classify the type of the data of 59 water samples.The discriminant rate (86.4％) of synthesis was obtained and the discriminant model was validated with examples.The results show that the combination of the principal component analysis and the multinomial Logistic regression model is feasible in water source identification.It not only eliminates the inherent influence of the constant ions,but also makes a certain degree of accuracy of the discriminant results.A new method is provided for discriminating water inrush source and it will provide an effective basis for preventing from and controlling of mine water.关键词
矿井水害/突水水源/主成分分析/多项Logistic回归模型Key words
mine water disaster/water bursting source/principal component analysis/regression model分类
天文与地球科学引用本文复制引用
张好,姚多喜,鲁海峰,薛凉,朱宁宁..基于主成分分析的多项Logistic回归模型的突水水源判别研究[J].高校地质学报,2017,23(2):366-372,7.基金项目
国家自然科学基金项目(51474008) （51474008）
安徽省自然科学基金项目(1508085QE89)共同资助 （1508085QE89）
