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。
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。
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。
To gain optimization parameters of hydro turbine PID governor, this paper interprets the approach of optimization designing that uses the Particle Swarm Optimization (PSO) algorithm.
为了保证获得最优水轮机PID调节器参数，本文研究了利用微粒群优化（PSO）算法进行参数优化设计的新方法。
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。
This paper introduces the principles and characteristics of Particle Swarm Optimization algorithm, and puts forward an improved particle swarm optimization algorithm.
介绍基本粒子群优化算法的原理、特点，并在此基础上提出了一种改进的粒子群算法。
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。
Particle swarm optimization is a kind of self-adaptive random algorithm based on group hunting strategy.
粒子群优化算法是一种基于种群搜索策略的自适应随机算法。
An improved particle swarm optimization (PSO) algorithm was designed. And a weighted ITAE index of turbine speed error was taken as the fitness function of the improved PSO algorithm.
提出了一种新的改进的粒子群优化算法，并以水轮机转速偏差的加权ITAE指标作为改进粒子群优化算法的适应度函数。
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。
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。
In this paper, a modified particle swarm optimization algorithm is presented to solve knapsack problem, and the detailed realization of the algorithm is illustrated.
本文提出了改进的粒子群算法求解背包问题，阐明了该算法求解背包问题的具体实现过程。
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。
Based on the swarm intelligence, Particle swarm optimization (PSO) algorithm is a kind of modern optimization method inspired by the research of the artificial life.
粒子群算法是基于群集智能、受到人工生命研究结果的启发而提出的一种现代优化方法。
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。
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。
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。
A pheromone-based discrete particle swarm optimization algorithm was proposed borrowing the idea of pheromone refresh mechanism of ant colony algorithm.
借鉴蚁群算法的信息素机制，提出了一种基于信息素机制的离散粒子群算法。
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。
Aimed at the characteristics of short-term electrical load forecasting, an algorithm based on multi-objective particle swarm optimization is proposed in the paper.
针对短期负荷预测的特点，提出一种基于多目标粒子群优化算法的短期电力负荷预测法。
A new method of public traffic line network optimization is presented by particle swarm algorithm.
针对公交线网优化问题，利用粒子群算法进行了研究。
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)。
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。
The chaos search based hybrid particle swarm optimization (PSO) algorithm is proposed in the paper to avoid the premature phenomenon of PSO, which is applied into the reactive power optimization.
应用粒子群优化算法(PSO)求解电力系统无功优化问题，提出基于混沌搜索的混合粒子群优化算法，以克服P SO容易早熟而陷入局部最优解的缺点。
To improve the searching performance of Particle Swarm Optimization (PSO), a modified PSO algorithm with flying time adaptively adjusted was proposed and named FAA-PSO algorithm.
为改善粒子群优化算法的搜索性能，提出一种飞行时间自适应调整的粒子群算法(FAA - P SO)。
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。
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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