基于多因子惯性权重的粒子群优化算法的-研究

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1、华中科技大学硕士学位论文Keywords：IntelligentoptimizationParticleswarmoptimizationalgorithmInertiaweightPressurevesseldesignVI万方数据华中科技大学硕士学位论文目录摘要............................................................................................................IVAbstract................................................

2、...........................................................V1绪论1.1课题研究背景......................................................................................(9)1.2课题研究现状....................................................................................(10)1.3本文的研究内容...............................

3、.................................................(11)1.4本文的结构.........................................................................................(12)2相关研究技术分析2.1优化算法概述....................................................................................(13)2.2常见的优化算法.............................

4、...................................................(14)2.3粒子群优化算法................................................................................(19)2.4粒子群优化算法的改进....................................................................(22)2.5本章小结..........................................................

5、...................................(25)3基于多因子自适应惯性权重的粒子群优化算法3.1改进惯性权重策略的经验借鉴........................................................(26)3.2改进粒子群算法的提出....................................................................(33)3.3改进粒子群算法的分析.................................................................

6、...(38)3.4本章小结.............................................................................................(42)4改进粒子群算法的实验研究4.1算法的实验环境................................................................................(43)VII万方数据华中科技大学硕士学位论文4.2算法的实验函数....................................................

7、............................(43)4.3算法参数测试实验............................................................................(45)4.4实验内容............................................................................