改进PSO算法在断层滑动参数反演中的研究与应用

Research and application of improved particle swarm optimizationalgorithm in fault sliding parameter inversion

利用地面大地测量数据反演断层的滑动速率等动态参数,是大地测量主要研究问题之一。本文首先提出了一种改进的粒子群算法,以此弥补标准粒子群算法可能局部最优解的不足,并通过模拟数据进行试验验证。然后以渭河盆地两条主要断裂为研究对象,利用地面GPS观测数据反演了秦岭北侧大断裂、临潼-长安断裂的三维滑动速率,并分析了两种算法的运行耗时。结果表明:改进的粒子群算法比标准粒子群算法耗时减少,收敛速度更快;本文所提算法反演得到的断层参数更符合真实的断裂条件,具有一定的实际应用价值。

One of the main research issues in geodesy is to use ground geodetic data to invert dynamic parameters such as fault sliding rate.We propose an improved particle swarm optimization algorithm to compensate for the shortcomings of the standard particle swarm algorithm,which may have local optimal solutions,and conduct experimental verification through simulated data.Later,taking the two main faults in the Weihe Basin as research objects,the three-dimensional sliding rates of the northern Qinling Fault and the Lintong Chang an Fault are inverted using ground GPS observation data,and the running time of the two algorithms is analyzed.The results show that the improved particle swarm optimization algorithm reduces the time consumption compared to the standard particle swarm optimization algorithm,and converges faster.The fault parameters obtained by the algorithm proposed in this article are more in line with real fault conditions and have certain practical application value.