摘要
对矿井突水水源的准确判别对于矿井安全生产有着重要的意义。本文提出采用基于蜻蜓算法和最小二乘支持向量机相结合的矿井突水水源预测方法,以Na^++K^+、Ca^2+、Mg^2+、Cl、SO4^2、HCO3等6种水中离子作为矿井突水水源模型的识别因素,利用收集的水样数据对最小二乘支持向量机进行训练和测试,研究结果表明基于蜻蜓算法和最小二乘支持向量机判别模型的计算结果与实际结果一致,而且具有良好的判别能力,其对提高矿井突水水源判别的准确性有着一定的借鉴意义。
It is very important to distinguish the source of mine water inrush for mine safety.In this paper,the dragonfly algorithm and least square support vector machine are used to predict the water source of mine water inrush.Six kinds of water ions such as Na^++K^+,Ca^2+,Mg^2+,Cl^,SO4^2,HCO3 are used as the identification factors of mine water inrush source model,and the least square support vector machine is trained and tested by using the collected water sample data.The research results show that the calculation results of the identification model based on dragonfly algorithm and least square support vector machine are consistent with the actual results,and had good discrimination ability,which can improve the accuracy of mine water inrush source identification.It had certain reference significance.
作者
吴兆立
WU Zhaoli(Jiangsu Vocational Institute of Architectural Technology,Xuzhou 221008,China)
出处
《中国矿业》
2021年第2期91-94,共4页
China Mining Magazine
基金
江苏建筑节能与建造技术协同创新中心基金项目“基于大数据的公共建筑能耗监测系统研究与应用”资助(编号:SJXTY1603)
江苏省现代教育技术研究2018年度智慧校园专项课题“高校智慧校园共享数据中心关键技术研究与应用”资助(编号:2018-R-66866)。
关键词
最小二乘支持向量机
蜻蜓算法
判别
矿井突水
least square support vector machine
dragonfly algorithm
identification
mine water inrush
