粒子群优化算法是群体智能中一个新的分支。
Particle Swarm Optimization(PSO)algorithm is one of embranchments of swarm intelligence.
论证了粒子群优化算法在边坡工程中的实用性。
It demonstrates the practicability of particle swarm optimization method in slope engineering.
粒子群优化算法是一种新型、高效的进化计算方法。
Particle swarm optimization algorithm is a new and efficient evolutionary computation method.
提出了一种新的自适应粒子群优化算法(AMPSO)。
A new self-adaptive particle swarm optimization (AMPSO) is presented.
论文研究了动态无功优化的数学模型和粒子群优化算法。
The paper studies the mathematical model of the dynamic reactive optimization and the particle swarm optimization (PSO).
模糊神经网络的学习算法采用的是快速的粒子群优化算法。
A fast stochastic global optimization algorithm, particle group optimization algorithm, was used for training the fuzzy neural network.
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。
Particle swarm optimization is a kind of self-adaptive random algorithm based on group hunting strategy.
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。
An improved particle swarm optimization algorithm embedded with greedy search for solution of unit commitment.
该文针对机组组合问题，提出了一种新的混合粒子群优化算法。
This paper proposes a new hybrid particle swarm optimization method for unit commitment problem.
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 for solving multiple Nash equilibrium solutions of bimatrix game is presented in this paper.
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。
A particle swarm optimization algorithm source code, this is a VB source languages, it is practical.
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 as a Swarm Intelligence algorithm, has strong global search capability, can be used for training neural network to overcome the defect of BP algorithm.
本文提出了一种基于粒子群优化算法的准确、快速和鲁棒性的点匹配方法。
In this paper, we propose an accurate and robust algorithm for solving the point matching problem using particle swarm optimization.
粒子群优化算法(PSO)是一种进化计算技术，是一种基于迭代的优化工具。
Particle Swarm optimization (PSO) is an evolutionary computation technique and an optimization tool based on iteration.
在研究粒子群优化算法生物特征的基础上，提出了粒子群优化算法的异步模式。
This paper proposes an asynchronous pattern from analyzing on the biologic character of particle swarm optimization.
提出了基于改进的二进制粒子群优化算法、以均衡负荷为目标的配电网重构方法。
A method based on improved binary particle swarm optimization (PSO) is proposed for distribution network reconfiguration with the objective of load balancing.
提出了一种新颖的基于分子动理论的粒子群优化算法(MMT - P SO)。
A novel particle swarm optimization based on theory of molecular motion (MMT-PSO) was proposed, and the population was regarded as molecule system.
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。
The classical Particle swarm optimization (PSO) algorithm is a powerful method to find the minimum of a numerical function, on a continuous definition domain.
为确定图像分割的最佳阈值，基于粒子群优化算法提出了一种多阈值图像分割方法。
To determine the optimal thresholds in image segmentation, a new multilevel thresholding method based on particle swarm optimization (PSO) is proposed in this paper.
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。
This paper introduces the principles and characteristics of Particle Swarm Optimization algorithm, and puts forward an improved particle swarm optimization algorithm.
基于粒子群优化算法(PSO)，提出一种求解含动态电压安全约束的预防控制新方法。
A particle swarm optimization (PSO) technique based novel approach for solving the dynamic voltage security constrained preventive control problem is proposed.
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.
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。
Aimed at the characteristics of short-term electrical load forecasting, an algorithm based on multi-objective particle swarm optimization is proposed in the paper.
粒子群优化算法应用于多极值点函数优化时，存在陷入局部极小点和搜寻效率低的问题。
Particle Swarm optimization (PSO) algorithm is a population-based global optimization algorithm, but it is easy to be trapped into local minima in optimizing multimodal function.
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。
This paper incorporates chaos optimization algorithm into the PSO algorithm, and propose a new particle swarm optimization algorithm based on chaos searching (CPSO).
提出了一种基于邻域拓扑粒子群优化算法(NTPSO)的大规模电力系统无功优化新算法。
A neighbourhood topology based particle swarm algorithm (NTPSO) is proposed for optimal reactive power dispatch and voltage control of power system.
提出了求解有等式约束优化问题的两种新粒子群优化算法，数值试验结果表明，算法是有效的。
To solve the equation constrained optimization problems, two new particle swarm optimization algorithms are presented. The experimental results show the algorithms are effective.
提出了求解有等式约束优化问题的两种新粒子群优化算法，数值试验结果表明，算法是有效的。
To solve the equation constrained optimization problems, two new particle swarm optimization algorithms are presented. The experimental results show the algorithms are effective.
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