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Modified electromagnetism-like algorithm and its application to slope stability analysis

ISSN号：1000-8993
期刊名称：《工业建筑》
时间：0
分类：TP301.6[自动化与计算机技术—计算机系统结构;自动化与计算机技术—计算机科学与技术] P642.22[天文地球—工程地质学;天文地球—地质矿产勘探;天文地球—地质学]
作者机构：[1]School of Resources and Safety Engineering, Central South University, Changsha 410083, China
相关基金：Project（10972238） supported by the National Natural Science Foundation of China; Project（2010ssxt237） supported by Graduate Student Innovation Foundation of Central South University, China; Project supported by Excellent Doctoral Thesis Support Program of Central South University, China

关键词：边坡稳定性分析, 混合算法, 电磁, 修改, 局部优化算法, 搜索区域, 应用, 最小安全系数, slope stability, hybrid optimization algorithm, complex method, electromagnetism-like algorithm, predatory searchstrategy

中文摘要：

在复杂方法(厘米) 和像电磁的算法(他们) 的劣势的看法，复杂像电磁的混合算法(CEM ) 被作为本地优化算法把复杂方法嵌进像电磁的算法建议。CEM 被采用在斜坡稳定性分析寻找最小的安全因素，结果证明 CEM 在他们和厘米上保持优点。它联合二的优点并且更稳定、有效。为进一步的改进，二个 CEM 混合算法基于食肉的搜索(PS ) ，策略被建议，哪个由修改算法和哪个被变化动态地调整的搜索区域组成限制。CEM-PS1 采用原来的食肉的搜索策略的理论框架。CEM-PS2 采用从食肉的搜索策略学习的限制区域的搜索的想法，但是算法结构更简单。CEM-PS1 和 CEM-PS2 被表明了比其它更有效、有效。至于在混合算法定位的复杂方法，优化能在 1 楲? 灯楴業慺楴湯愠杬牯瑩浨的集中精确被完成； ????\

英文摘要：

In the view of the disadvantages of complex method （CM） and electromagnetism-like algorithm （EM）, complex electromagnetism-like hybrid algorithm （CEM） was proposed by embedding complex method into electromagnetism-like algorithm as local optimization algorithm. CEM was adopted to search the minimum safety factor in slope stability analysis and the results show that CEM holds advantages over EM and CM. It combines the merits of two and is more stable and efficient. For further improvement, two CEM hybrid algorithms based on predatory search （PS） strategies were proposed, both of which consist of modified algorithms and the search area of which is dynamically adjusted by changing restriction. The CEM-PS1 adopts theoretical framework of original predatory search strategy. The CEM-PS2 employs the idea of area-restricted search learned from predatory search strategy, but the algorithm structure is simpler. Both the CEM-PS1 and CEM-PS2 have been demonstrated more effective and efficient than the others. As for complex method which locates in hybrid algorithm, the optimization can be achieved at a convergence precision of 1 ×10-3, which is recommended to use.

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