An improved artificial bee colony algorithm for inversion of seismic source parameters using GPS observation data

Objectives: With the improvement of the accuracy of geodetic observation data, the inversion of seismic source parameters has put forward higher requirements on the performance of optimization algorithms. Methods: A novel artificial bee swarm algorithm is proposed to invert the seismic source parameters for the seismic source parameter optimization problem. Subsequently, based on the limitations of the following bee search module, the algorithm is improved by introducing the variance component of the difference between the global optimal individuals and the population individuals after the hiring bee stage update. To verify the effectiveness of the algorithm improvement, the performance of the standard artificial bee algorithm, the improved artificial bee algorithm and the multi-peak particle swarm algorithm are evaluated through experimental tests. Results: simulated earthquake simulation experiments for eight groups of different types of faults show that the improved artificial bee algorithm outperforms the standard artificial bee algorithm and the multi-peak particle swarm algorithm in terms of accuracy and stability; finally, the algorithm is applied to the 2013 Lushan earthquake and 2017 Bodrum-Kos earthquake. Conclusions: The results show that the improved artificial swarm algorithm has good practicality and reliability.