Abstract：There are problems in micro-seismic source localization using the multi-objective intelligent optimization algorithm: the rationality of model combination is not elucidated, it is easy to fall into local optimal solutions, and the large fluctuation of localization results. To solve these problems, we design four different mathematical models for micro-seismic source localization based on the arrival time difference model and the arrival time difference quotient model, and six multi-objective optimization localization models are constructed by combining two and two. We design three sets of micro-seismic source forward simulation experiments and one set of engineering verification experiments based on different network shapes(3D polyhedral, 2D rectangular, and 1D linear), and introduce multi-objective ant lion optimization(MOALO) algorithm. We apply several statistical indicators to evaluate the advantages and disadvantages of the localization effect of each model combination. The results show that the combination of mathematical models(TDA-P1, TDQA) and the MOALO algorithm can obtain high accuracy of micro-seismic source localization, and the robustness of the models is better than other model combinations and traditional multi-objective localization methods, which has certain application value in the field of micro-seismic monitoring.
CHEN Guoqing,PANG Cong,XIANG Ya et al. Mathematical Model Combination in Micro-Seismic Source Localization Based on Multi-Objective Ant Lion Optimization[J]. jgg, 2023, 43(10): 1074-1079.
