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Application of Particle Swarm Optimization to Seismic Location

机译:粒子群优化在地震位置的应用

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摘要

The particle swarm optimization (PSO) is an adaptive optimization based on swarm intelligence. The basic principle and the method of it being used in seismic location were introduced. To get a more accurate result, the objective function is the residual square sum of the observational travel-time and theoretical travel-time of the same earthquake return two stations. Compared with Genetic Algorithm on Seismic Location, PSO, after numerous experiments, proved its distinct superiority to locate the hypocenter more quickly and accurately. PSO is potentially useful for seismic location.
机译:粒子群优化(PSO)是基于群体智能的自适应优化。介绍了其在地震位置使用的基本原理和方法。为了获得更准确的结果,目标函数是观察旅行时间的残余平方和,同一地震的理论旅行时间返回两个站。与遗传算法相比,地震位置,PSO在众多实验之后,证明了其独特的优势,以更快,更准确地定位斜视。 PSO可能对地震位置有用。

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