...为克服粒子群算法存在的早熟问题,采用自适应变异的粒子群算法(adaptive mutation particle swarm optimization algorithm,AMPSO)对配电网中的DG选址和定容进行了优化。
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本文提出了一种新的基于群体适应度方差自适应变异的粒子群优化算法(AMPSO)。
A new adaptive mutation particle swarm optimizer (AMPSO), which is based on the variance of the population's fitness is presented.
提出一种新的粒子群算法(PSO)边界变异策略——最小值边界变异。
A new boundary mutation strategy, the minimum boundary mutation, is presented based on Particle Swarm Optimization (PSO).
对自适应粒子群算法引入变异算子，并对其进行改进，将其应用到淋巴瘤形态参数的分类问题上。
This paper adds mutation operator to adaptive PSO and apply it in the lymphoma morphology parameter classifier problems.
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