An Expert Artificial Intelligence Model for Discriminating Microseismic Events and Mine Blasts

To reduce the workload and misjudgment of manually discriminating microseismic events blasts in mines, an artificial intelligence model called PSO-ELM, based on extreme learning machine (ELM) optimized by particle swarm optimization (PSO) algorithm, was applied this study. Firstly, difference between mine previous research results, 22 seismic parameters were selected as discrimination feature their correlation analyzed. Secondly, 1600 randomly from database monitoring system Fankou Lead-Zinc Mine to form a sample dataset. Then, optimal established investigating parameters. Finally, performance tested using dataset, it compared with original ELM other commonly used intelligent models. The results indicate that PSO-ELM is best. values six evaluation indicators are close value, which shows has great potential for blasts. obtained can provide new method blasts, significance ensure safe smooth operation mines.