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搜索资源 - An Improved Particle Swarm Optimization Algorithm
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提出了一种基于反向学习机制的改进量子粒子群算法，采用反向学习机制增加种群的多样性，使搜索效率有了较大的提高，有效地避免了算法早熟收敛。-An improved quantum particle swarm optimization (QPSO) based on reverse
learning is presented in this paper, which adopts reverse learning to increase
the diversity of the popula
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为进一步提高螺栓遗传算法的优化效率，加速寻优过程，提出基于对立策略的螺栓遗传算法。该算法在种群初始化阶段和变异阶段均用对立取代随机方式，提高产生解的质量。利用测试函数对算法的效率进行检验，将其与差分算法、遗传算法、粒子群算法和螺栓遗传算法进行对比，结果表明，新算法具有更快的收敛速度和更高的求解精度。-In order to improve the performance of Stud Genetic Algorithm(SGA) and accelerate the convergence s
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针对现有改进和声搜索算法(IHS) 的不足，提出一种自适应和声粒子群搜索算法(AHSPSO).-For the purpose of avoiding the disadvantage of improved harmony search (IHS) algorithm, an adaptive harmony
search-particle swarm optimization (AHSPSO) algorithm is presented.
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Particle swarm optimization is a heuristic global optimization method and also an optimization algorithm, which is
based on swarm intelligence. It comes from the research on the bird and fish flock movement behavior. The algorithm is
widely use
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This paper proposes an improved maximum power
point tracking (MPPT) method for the photovoltaic (PV) system
using a modifi ed particle swarm optimization (PSO) algorithm.
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遗传算法优化BP神经网络、改进的模糊C-均值聚类、遗传算法（粒子群算法、人工鱼群算法等）的投影寻踪模型等遗传算法的简单集合。-Genetic algorithm to optimize the BP neural network, an improved fuzzy C- average clustering and genetic algorithm,(particle swarm optimization (pso), artificial fish algorithm, etc.) of
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基于变异策略的改进型花朵授粉算法，里边集成了粒子群算法、蝙蝠算法以及定向变异策略，进行对比(An improved flower pollination algorithm based on mutation strategy, which integrates particle swarm optimization, bat algorithm and directional mutation strategy, is compared.)
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改进量子粒子群算法，用于优化支持向量机参数，用IRIS数据验证(An improved quantum particle swarm optimization (QPSO) algorithm is used to optimize the parameters of support vector machine (SVM), which is validated by IRIS data.)
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