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首页> 外文会议>International Conference on Signal Processing, Communication, Power and Embedded System >APPLICATION OF ENHANCED PARTICLE SWARM OPTIMIZATION FOR RESIDUAL GRAVITY INVERSION OVER SEDIMENTARY BASINS
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APPLICATION OF ENHANCED PARTICLE SWARM OPTIMIZATION FOR RESIDUAL GRAVITY INVERSION OVER SEDIMENTARY BASINS

机译：增强粒子群优化在沉积盆地上剩余重力逆变的应用

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Particle Swarm Optimization (PSO) is one of the latest evolutionary optimization techniques by nature. It has the better ability of global searching and has been. Due to the linear decreasing of inertia weight in PSO the convergence rate becomes faster, which leads to the minimal make span time when used for scheduling. To make the convergence rate faster, the PSO algorithm is improved by modifying the inertia parameter, such that it produces better performance and gives an optimized result. In order to overcome the problem of trapping at local minima, an efficient PSO algorithm is attempted that can improve the exploration competence of the standard PSO. Initially, the PSO is tested and then validated on synthetic gravity anomalies generated over the sedimentary basin without and with Gaussian noise. On the performance of this algorithm based on the convergence characteristics, and their robustness, PSO applied to field data obtained from Gediz graben, Western Anatolia. The results simulated by proposed PSO provides consistent that are well correlated to results obtained from other methods.
机译：粒子群优化（PSO）是自然最新的进化优化技术之一。它具有更好的全球搜索能力。由于PSO中的惯性重量的线性降低，收敛速率变得更快，这导致用于调度时的最小制作跨度时间。为了使收敛速率更快，通过修改惯性参数来提高PSO算法，使得它产生更好的性能并提供优化的结果。为了克服局部最小值的捕获问题，尝试了一种有效的PSO算法，可以改善标准PSO的勘探能力。最初，测试PSO，然后在沉积盆地产生的合成重力异常上验证，没有高斯噪音。基于收敛特性的该算法的性能及其鲁棒性，PSO应用于从西部阿纳托利亚GEDIZ Graben获得的现场数据。通过提出的PSO模拟的结果提供了一致的，其与从其他方法获得的结果良好相关。

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