Shuffled Frog Leaping Algorithm Based on Grey Prediction Theory

被引：0

作者：

Du J. ^{[1
]}

Yuan Z. ^{[1
]}

Wang J. ^{[1
]}

机构：

[1] Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin

来源：

Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2017年 / 32卷 / 15期

关键词：

Grey prediction; Mutation operator; Optimal design; Shuffled frog leaping algorithm;

D O I：

10.19595/j.cnki.1000-6753.tces.160634

中图分类号：

学科分类号：

摘要：

To enhance the performance of shuffled frog leaping algorithm in solving optimization problems, a new model for hybrid leapfrog algorithm based on grey prediction theory was proposed. The algorithmic evolution model was adjusted to strengthen the ability to exchange the global information in the process of evolution. Then the algorithm implemented the mobile step self-adaption adjustment through introduced mobile step mutation operator. The mutation operator was controlled by the different stages of evolution and the optimal solution progress speed in the process of evolution obtained by grey prediction theory and the fuzzy control thoughts. The advantages of the improved hybrid leapfrog algorithm, such as the accuracy, convergent speed and success rate, and the feasibility of grey prediction theory in the field of algorithm improvement, is verified by comparison with the basic shuffled frog leaping algorithm and the known improved algorithm on performance through six standard test functions. Finally, the practicability of the improved algorithm is proved by applying it to 10 kV oil-immersed distribution transformer optimization design works. © 2017, The editorial office of Transaction of China Electrotechnical Society. All right reserved.

引用

页码：190 / 198

页数：8

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