• An improved particle swarm optimization algorithm embedded with greedy search for solution of unit commitment.

    求解机组组合问题的嵌入贪婪搜索机制的改进粒子群优化算法。

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  • Particle Swarm Optimization (PSO) algorithm has existed premature convergence for multimodal search problems.

    粒子群优化(PSO)算法对于多峰搜索问题一直存在早熟收敛问题。

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  • Particle swarm Optimization (PSO) algorithm is based on swarm intelligence theory.

    粒子群优化(PSO)算法是基于群体智能理论的优化算法。

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  • Particle Swarm Optimization (PSO) algorithm for solving multiple Nash equilibrium solutions of bimatrix game is presented in this paper.

    提出了一种求解双矩阵对策多重纳什均衡解的粒子群优化算法。

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  • Particle Swarm Optimization (PSO) algorithm is a powerful method to find the extremum of a continuous numerical function.

    微粒群优化算法是求解连续函数极值的一个有效方法。

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  • Particle Swarm Optimization(PSO)algorithm is one of embranchments of swarm intelligence.

    粒子群优化算法是群体智能中一个新的分支。

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  • A particle swarm optimization algorithm source code, this is a VB source languages, it is practical.

    一种粒子群优化算法源程序,这是一个VB语言编制的源程序,很实用。

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  • The standard particle swarm optimization algorithm as a random global search algorithm, because of its rapid propagation in populations, easily into the local optimal solution.

    标准的粒子群优化算法作为一种随机全局搜索算法,因其在种群中传播速度过快,易陷入局部最优解。

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  • Particle swarm optimization algorithm is a new and efficient evolutionary computation method.

    粒子群优化算法是一种新型、高效的进化计算方法。

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  • The classical Particle swarm optimization (PSO) algorithm is a powerful method to find the minimum of a numerical function, on a continuous definition domain.

    经典的粒子群优化算法是一个在连续的定义域内搜索数值函数极值的很有效的方法。

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  • The computer simulation results showed that the proposed algorithm was superior to original particle swarm optimization algorithms and was effective in separating nonlinear blind sources.

    计算机仿真结果表明该算法的收敛性能优于粒子群优化算法,并且在非线性盲信号分离中是有效的。

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  • Particle Swarm Optimization as a Swarm Intelligence algorithm, has strong global search capability, can be used for training neural network to overcome the defect of BP algorithm.

    然而在粒子群优化算法中,早熟现象时有发生,从而制约了算法的性能。

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  • An algorithm for discretization based on Particle swarm optimization (PSO) is presented, which can settle the problem of continuous attributes discretization in systema modeling perfectly.

    提出了一种基于微粒群优化(PSO)算法的连续属性离散化方法,很好的解决了建模过程中连续属性的离散化问题。

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  • Neural network based on particle swarm optimization algorithm applied in the soil moisture characteristic curve application.

    说明:基于粒子群的神经网络优化算法的应用,在土壤水分特征曲线中的应用。

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  • An adaptive particle swarm optimization (APSO) algorithm to solve the AGC unit dispatch problem in power system is proposed.

    提出了一种基于自适应型粒子群优化算法(APSO)的自动发电控制(agc)机组调配方案。

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  • In this paper, we review ant colony algorithm and particle swarm optimization.

    本文讨论了群集智能的两种算法,蚁群智能与微粒群智能。

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  • This paper brings forward the binary improved particle swarm optimization algorithm for decision of loans combinatorial optimization problem, and illustrates the detailed realization of the algorithm.

    针对贷款组合优化决策模型的求解问题,论文提出了用于求解该问题的二进制粒子群算法,并阐明了算法的具体实现过程。

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  • This algorithm can solve the problem of low precision and divergence of basic particle swarm optimization algorithm, so it has higher efficiency of search.

    该算法能克服基本微粒群优化算法精度较低,易发散的缺点,有较高的搜索效率。

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  • Considering that the particle swarm optimization (PSO) algorithm is quite simple and easy to implement, it was used to estimate the nonlinear model parameters in this paper.

    粒子群算法操作简便、容易实现且全局搜索功能较强,适用于非线性参数估计。

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  • Aiming at the stagnation exists in the cooperative particle swarm optimization, presents a new kind of the cooperative particle swarm optimization algorithm based on particles spatial extension.

    针对协同微粒群优化存在的停滞现象,提出了一种新的基于粒子空间扩展的协同微粒群优化算法。

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  • A rolling load distribution optimization algorithm of tandem cold mill was designed using particle swarm optimization algorithm.

    利用粒子群算法设计了一种冷连轧轧制负荷分配的优化方法。

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  • On the basis of analyzing the particle swarm optimization and introducing the idea of sub-swarms, a particle swarm optimization algorithm with dynamic sub-swarms (DPSO) is proposed.

    在分析基本微粒群优化算法的基础上,引进分群思想,提出了一种动态分群的微粒群优化算法(DPSO)。

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  • The basic and typical algorithm of swarm intelligence is particle swarm optimization and Ant colony oprimation.

    目前,群智能理论研究领域有两种主要的算法:微粒群优化算法和蚁群优化算法。

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  • For the bilevel programming model, this paper designs a heuristic solution algorithm based on particle swarm optimization technique.

    然后基于粒子群优化技术,设计一个启发式求解算法。

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  • A new algorithm of swarm intelligence, Particle swarm Optimization (PSO), which is an algorithm of simple implementation and fast convergence with few parameters, is introduced in this paper.

    介绍了一种新的集群智能算法-微粒群算法(PSO),该算法具有实现简单、参数少且收敛快的特点。

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  • This paper incorporates chaos optimization algorithm into the PSO algorithm, and propose a new particle swarm optimization algorithm based on chaos searching (CPSO).

    文章把混沌优化搜索技术引入到P SO算法中,提出了基于混沌搜索的粒子群优化算法。

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  • This paper incorporates chaos optimization algorithm into the PSO algorithm, and propose a new particle swarm optimization algorithm based on chaos searching (CPSO).

    文章把混沌优化搜索技术引入到P SO算法中,提出了基于混沌搜索的粒子群优化算法。

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