基于PCA分析的突水水源Fisher判别模型
|
摘要
为有效快速地判断突水水源的位置,预防突水事故的发生,针对不同水层水质差异性,选取6大常规水化学离子作为判别因子,结合PCA分析法和Fisher判别法建立矿井突水水源判别模型。以潘三煤矿新生界下含和煤系水共20个水样为例,对该模型进行验证,并与BP神经网络判别模型进行对比,得出准确率达100%,说明该方法的可行性、准确性。
In order to effectively and quickly determine the location of water source, prevent the occurrence of sudden water accident. Six conventional water chemical ions were selected as the discriminanted factor for different water quality. Using PCA analysis method, Fisher discriminant method was adopted to establish the discriminant model of mine water source water source. The model is verified by the 20 water sample data in the Cenozoic lower part and coal departments of Pansan coal mine. Compared with BP neural network discriminant model, the accuracy rate reaches 100%,indicating the feasibility and accuracy of this method.
In order to effectively and quickly determine the location of water source, prevent the occurrence of sudden water accident. Six conventional water chemical ions were selected as the discriminanted factor for different water quality. Using PCA analysis method, Fisher discriminant method was adopted to establish the discriminant model of mine water source water source. The model is verified by the 20 water sample data in the Cenozoic lower part and coal departments of Pansan coal mine. Compared with BP neural network discriminant model, the accuracy rate reaches 100%,indicating the feasibility and accuracy of this method.
引文
[1]刘伟韬.矿井水害与防治[M].北京:煤炭工业出版社,2016.
[2]魏久传,肖乐乐,牛超,等.2001-2013年中国矿井水害事故相关性因素特征分析[J].中国科技论文,2015,10(3):336-341,369.
[3]赵国红,黄健敏.煤矿突水水源判别方法的应用研究[J].煤炭技术,2016,35(9):150-152.
[4]祝翠,钱家忠,周小平,等.BP神经网络在潘三煤矿突水水源判别中的应用[J].安徽建筑工业学院学报:自然科学版,2010,18(5):35-38.
[5]钱兆明,任高峰,褚夫蛟,等.基于PCA法和Fisher判别分析法的岩体质量等级分类[J].岩土力学,2016,37(S2):427-432,441.
[6]骆行文,姚海林.基于主成分分析的岩石质量综合评价模型与应用[J].全国岩土力学数值分析与解析方法研讨会,2010,31(S2):452-455.
[7]邓清海,曹家源,张丽萍,等.基于主成分分析的矿井突水水源Bayes判别模型[J].水文地质工程地质,2014,41(6):20-25.
[8]潘婧.基于Matlab的潘三矿地下水水化学场分析及突水水源判别模型[D].合肥:合肥工业大学,2010.
[2]魏久传,肖乐乐,牛超,等.2001-2013年中国矿井水害事故相关性因素特征分析[J].中国科技论文,2015,10(3):336-341,369.
[3]赵国红,黄健敏.煤矿突水水源判别方法的应用研究[J].煤炭技术,2016,35(9):150-152.
[4]祝翠,钱家忠,周小平,等.BP神经网络在潘三煤矿突水水源判别中的应用[J].安徽建筑工业学院学报:自然科学版,2010,18(5):35-38.
[5]钱兆明,任高峰,褚夫蛟,等.基于PCA法和Fisher判别分析法的岩体质量等级分类[J].岩土力学,2016,37(S2):427-432,441.
[6]骆行文,姚海林.基于主成分分析的岩石质量综合评价模型与应用[J].全国岩土力学数值分析与解析方法研讨会,2010,31(S2):452-455.
[7]邓清海,曹家源,张丽萍,等.基于主成分分析的矿井突水水源Bayes判别模型[J].水文地质工程地质,2014,41(6):20-25.
[8]潘婧.基于Matlab的潘三矿地下水水化学场分析及突水水源判别模型[D].合肥:合肥工业大学,2010.