利用粒子群的优化算法，建立侵彻子母弹最佳抛撒高度的求解模型，并进行了仿真计算。
By using Particle Swarm Optimization (PSO), a model was built up for calculating the optimum dispersion height of intrusive submunition dispenser, and mathematical simulation was carried out.
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.
粒子群算法是一类基于群智能的随机优化算法。
Particle swarm algorithm was an optimized algorithm based on swarm intelligence.
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.
针对工程中的优化问题，将粒子群算法与死亡罚函数法相结合，提出一种求解有约束问题的优化算法。
Aiming at the optimization problem in engineering, this paper proposes a new algorithm for con-strained optimization problem by combining PSO with death penalty.
粒子群优化(PSO)算法是基于群体智能理论的优化算法。
Particle swarm Optimization (PSO) algorithm is based on swarm intelligence theory.
优化结果说明在这个例子中粒子群优化有更好的表现，这也说明两种方法在问题的多维空间中搜索最优解的方式不同。
The result shows that particle swarm optimization performs better in this case, which implies that the two methods traverse the problem hyperspace differently.
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。
An adaptive particle swarm optimization (APSO) algorithm to solve the AGC unit dispatch problem in power system is proposed.
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.
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(PSO)算法是一类新兴的随机优化技术，其思想来源于人工生命和演化计算理论。
Particle swarm optimization (PSO) is a new stochastic optimization technique originating from artificial life and evolutionary computation.
提出了基于混合粒子群优化的时变时滞系统辨识方法。
A method for the identification of time-varying delay systems using hybrid particle swarm optimization is proposed.
借鉴蚁群优化算法和粒子群优化算法的思想，提出了一种用于求解约束优化问题的连续域蚁群算法。
Using the idea of both ant colony optimization algorithm and particle swam optimization algorithm, a continuous domains ant colony algorithm for solving constrained optimization problem was proposed.
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。
Neural network based on particle swarm optimization algorithm applied in the soil moisture characteristic curve application.
提出了一种新颖的基于粒子群优化和多级检测的混合算法的多用户检测器。
A novel hybrid algorithm approach that employs a particle swarm optimization (PSO) and a multistage detection for the multiuser detection problem (PSOMSD) is proposed.
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.
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.
提出了改进的粒子群优化算法。
In this paper, a modified particle swarm optimization method is proposed.
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.
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。
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.
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.
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.
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.
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。
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.
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.
本论文提出的多目标粒子群算法优化锅炉可调运行参数在锅炉燃烧优化领域还不多见。
It is an unusual case to use MOPSO to optimize operation parameters of boiler in the field of boiler combustion optimization.
本论文提出的多目标粒子群算法优化锅炉可调运行参数在锅炉燃烧优化领域还不多见。
It is an unusual case to use MOPSO to optimize operation parameters of boiler in the field of boiler combustion optimization.
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