基于改进布谷鸟搜索算法的矿震震源定位方法研究

Research on mining earthquake source localization method based on improved cuckoo search algorithm

矿震震源定位精度对于矿山监测十分重要,为进一步加快算法的收敛速度,提升算法的稳定性,提高定位的准确度,提出一种基于改进布谷鸟搜索算法的震源定位算法(ICS).该算法首先利用差值绝对值得到目标函数,然后在布谷鸟搜索算法的基础上,通过引入基于自适应度调节的步长比例因子和动态变化的发现概率,以改进选取鸟巢位置的方式,最后使用改进布谷鸟搜索算法对目标函数寻优求解.通过模拟实验比较可得,当速度在±1%、±3%和±5%的范围内浮动时,ICS算法的定位精度均高于原始布谷鸟搜索算法(CS)、海鸥优化算法(SOA)、灰狼优化算法(GWO)和非线性最小二乘法(NLS),相同情况下,ICS算法比原始CS算法的收敛速度提升52%.通过对内蒙古某煤矿的微震事件进行定位分析,ICS算法的定位误差由原始CS算法的40.1 m下降为23.3 m,定位精度提高了42%.验证了ICS算法具有更高的准确性和更快的收敛性.

The accuracy of seismic source location is very important for mine monitoring.In order to further accelerate the convergence speed,improve the stability of the algorithm and improve the accuracy of location,a seismic source location algorithm based on the Improved Cuckoo Search(ICS) algorithm is proposed.The algorithm firstly uses the absolute difference value to obtain the objective function.And then,based on the cuckoo search algorithm,it introduces the step scale factor based on adaptive adjustment and the discovery probability of dynamic changes to improve the way of selecting the bird's nest position.Finally,it uses the improved cuckoo search algorithm to optimize the objective function.Through the simulation experiment comparison can be obtained,the accuracy of ICS algorithm is higher than that of original Cuckoo Search(CS) algorithm,Seagull Optimization Algorithm(SOA),Grey Wolf Optimization Algorithm(GWO) and Nonlinear Least Square(NLS) method when the speed is floating within the range of ±1%,±3% and ±5%.The convergence rate of ICS algorithm is 52% higher than the original CS algorithm.Based on the location analysis of a microseismic event in a coal mine in Inner Mongolia,the location error of ICS algorithm is reduced from 40.1 m to 23.3 m,and the location accuracy is increased by 42%.It is proved that ICS algorithm has higher accuracy and faster convergence.