基于模糊推理的粒子群优化算法

被引：9

作者：

史旭栋 ^{[1
]}

高岳林 ^{[2
]}

韩俊茹 ^{[1
]}

机构：

[1] 宁夏大学数学统计学院

[2] 北方民族大学信息与系统科学研究所

来源：

河南师范大学学报(自然科学版) | 2017年 / 45卷 / 02期

关键词：

粒子群优化; 模糊推理; 信息共享;

D O I：

10.16366/j.cnki.1000-2367.2017.02.020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

针对无约束优化问题,提出了基于模糊推理的粒子群优化算法,该算法针对粒子群优化算法搜索能力的不足,先引入平均粒子,然后引入模糊推理来改进粒子群的速度更新公式,再利用模糊推理动态地改进算法惯性权重和速度更新公式的权重因子,再结合混沌扰动增加算法后期的局部搜索能力.数值试验采用12个测试函数并有5个算法进行对比,数值试验证明,改进算法的搜索能力有较大的提高.

引用

页码：108 / 118

页数：11

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