基于因子分析的突水水源类型判别的研究

Research on discrimination of mine water bursting source based on factor analysis

调研收集了顾北煤矿的水文地质资料,运用SPSS因子分析方法对各种水化学离子指标进行浓缩,抽取和综合成主因子,以少数变量最大程度地反映信息的完整性。将适合模型判别的因子运用Bayesian多类线性识别模型,分别对煤系砂岩裂隙水和太灰充水含水层水的待判水样进行了判别,结果表明:砂岩裂隙水和太灰水综合判别准确率达86.9%,与直接运用Bayesian模型判别相比,其分析过程的复杂性降低,准确性较高。

Through the investigation and collection of hydrogeological data in the Gubei Coal Mine,by using SPSS factor analysis method,various hydrochemical ion indexes were concentrated,extracted and synthesized into principal factors,to use a few variables to reflect the completeness of information to the greatest extent.The factors suitable for model discrimination were applied to the Bayesian multi-class linear identification model,and the samples of sandstone fractured water and limestone water were distinguished respectively.The results show that the comprehensive discrimination accuracy rate of the sandstone fractured water and limestone water is 86.9%.Compared with the direct Bayesian discrimination,the complexity of the analysis process is decreased and the discrimination is more accurate.