| 板状体磁异常数据反演的PSO算法 |
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| 引用本文： | 吴招才,刘天佑.板状体磁异常数据反演的PSO算法[J].物探与化探,2009,33(2):194-198. |
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| 作者姓名： | 吴招才 刘天佑 |
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| 作者单位： | 1. 国家海洋局,第二海洋研究所,浙江,杭州,310012;中国地质大学,地球物理与空间信息学院,湖北,武汉,430074
2. 中国地质大学,地球物理与空间信息学院,湖北,武汉,430074 |
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| 摘 要： | 粒子群优化(PSO)算法是根据鸟群觅食过程中的迁徙和群集模型而提出的用于解决优化问题的算法，是一类随机全局优化技术，它通过粒子间的相互作用搜索复杂空间中的最优区域，其优势在于效率高，且又简单易实现。本文讨论了PSO算法用于板状体磁异常数据反演的方法，并与遗传算法(GA)进行了比较。理论和实测磁异常数据反演的结果表明，PSO算法具有更高的找寻最优解效率，是一种很有潜力的位场反演工具。
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| 关 键 词： | PSO算法，GA算法，板状体磁异常，反演 |
HE APPLICATION OF PARTICLE SWARM OPTIMIZATION TO THE INVERSION OF MAGNETIC ANOMALY DATA OF TABULAR BODIES |
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| WU Zhao-cai,LIU Tian-you.HE APPLICATION OF PARTICLE SWARM OPTIMIZATION TO THE INVERSION OF MAGNETIC ANOMALY DATA OF TABULAR BODIES[J].Geophysical and Geochemical Exploration,2009,33(2):194-198. |
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| Authors: | WU Zhao-cai LIU Tian-you |
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| Institution: | Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China |
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| Abstract: | Particle swarm optimization (PSO), based on the idea of a swarm of birds searching for foods, is a new global optimization scheme. It can find optimal regions in searching space through the interaction of individuals in a population of particles, with the advantages of efficient searching and easy implementation. This paper deals with the inversion of the magnetic data of tabular bodies by means of PSO in comparison with the genetic algorithm (GA). The inversion results of theoretical and practical data show that PSO can find the optimal solution with fairly high efficiency. |
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| Keywords: | particle swarm optimization genetic algorithm magnetic data of tabular bodies inversion |
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