Research on microseismic source localization based on improved particle swarm optimization algorithm

Accurate microseismic source localization is crucial for detecting potential geological hazards during mining operations, ensuring the safe and efficient progress of excavation activities. The accuracy and reliability of source localization are closely linked to the selection of appropriate algorithms. While the Particle Swarm Optimization (PSO) algorithm offers the advantage of fast convergence, it is prone to premature convergence and low localization accuracy when directly applied to source localization. To address these issues, this study employs chaotic mapping to replace traditional methods for initializing the particle population, enhancing population diversity. The proposed method is validated through engineering case studies. The results demonstrate that, compared to the traditional PSO algorithm, the chaotic mapping-based improved PSO algorithm achieves faster convergence and superior optimization capabilities, making it suitable for solving practical engineering problems.