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中文摘要：
分析了含维变异算子的粒子群优化算法全局搜索能力与收敛速度的矛盾,提出了动态惯性权重向量和维变异的改进粒子群优化算法。算法首先定义了维多样性的概念,根据维多样性的情况动态地调整惯性权重向量,并对维多样性最差的维进行变异。4个典型测试函数的仿真实验说明该算法具有更强的全局搜索能力和更快的收敛速度。
英文摘要：
The contradiction of the global exploration and convergence speed of particle swarm optimization with dimension mutation operator is analyzed,and an improved algorithm（WPSO） is proposed by modifying PSO with dimension mutation based on dynamical inertial weight vector.In the proposed algorithm,the concept of dimension diversity is defined and inertial weight vector will be updated dynamically according to dimension diversity.The mutation operates on dimension whose dimension diversity is the worst.The simulation on four typical test functions indicates that the proposed algorithm has more powerful global exploration ability and faster convergence speed.
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