针对当前采矿工程中矿井风网风量优化调节效果不够理想的缺陷,研究提出一种风量优化调节模型,并采用优化的灰狼优化算法(Grey Wolf Optimization,GWO)对其进行求解,完成矿井风网风量智能优化调节.结果显示,MGW O算法求解的风量优化平均值为216.4kW,平均运行时间为132.6s,均优于其他两种算法.上述结果说明,研究提出的MGWO对矿井风网风量优化调节模型的求解效率与精度更高,对风网风量优化调节的效果更好,能够有效调节风网风量,保证采矿工程安全性.
Application of MGWO Based on Mining Engineering Safety in Optimal Adjustment of Mine Ventilation Network
In response to the deficiency of insufficient optimization and regulation effect of mine air network air volume in current mining engineering,a model for air volume optimization and regulation is proposed,and an optimized Grey Wolf Optimization(GWO)algorithm is used to solve it,achieving intelligent optimization and regulation of mine air network air volume.The results show that the aver-age air volume optimization value solved by the MGWO algorithm is 216.4kW,and the average operat-ing time is 132.6s,both of which are superior to the other two algorithms.The above results indicate that the MGWO proposed in the study has higher efficiency and accuracy in solving the optimization and adjustment model of mine air network air volume,and has a better effect on the optimization and adjust-ment of air network air volume.It can effectively regulate the air network air volume and ensure the safety of mining engineering.
Grey Wolf Optimization algorithmmining engineeringmine ventilation networkair volume optimization