矿业科学学报2024，Vol.9Issue(2)：233-242,10.DOI:10.19606/j.cnki.jmst.2024.02.010
基于优化领先狼群算法的微震源定位研究
Research on microseismic source localization based on optimized leading wolfpack algorithm
李晓燕 1张明伟 1宋雷 1庞迎春 2张结如2
作者信息
- 1. 中国矿业大学力学与土木工程学院,江苏徐州 221116||深地工程智能建造与健康运维全国重点实验室,江苏徐州 221116
- 2. 淮北矿业集团有限责任公司,安徽准北 235000
- 折叠
摘要
Abstract
In order to analyze the impact of different heuristic methods on the precision of microseismic source localization,an optimized Dominant Wolf Pack Algorithm(DWPA)is proposed.This algorithm builds upon the Dominant Wolf Pack Algorithm and introduces adjustments to two parameters,namely the search step size and the siege step size,enhancing its ability to escape local optima during the search process.The effectiveness of the optimized DWPA is validated through theoretical model inversion and engineering numerical analysis.A comparative study with commonly used heuristic algo-rithms,Particle Swarm Optimization(PSO)and Simulated Annealing(SA),reveals that the optimized DWPA exhibits faster convergence,higher accuracy,and reduced sensitivity to P-wave velocity er-rors.This research provides new insights for the application of intelligent heuristic algorithms in micro-seismic source localization.关键词
微震源定位/微震检测/领先狼群算法/粒子群算法/模拟退火算法Key words
microseismic source localization/microseismic detection/lesding wolf pack algorithm(LWA)/particle swarm optimization(PSO)/simulated Annealing algorithms(SA)分类
矿业与冶金引用本文复制引用
李晓燕,张明伟,宋雷,庞迎春,张结如..基于优化领先狼群算法的微震源定位研究[J].矿业科学学报,2024,9(2):233-242,10.
