通过上述的研究，提出了两种改进的粒子群算法。
Through this research, the paper give two modified particle swarm algorithms.
提出一种基于局部与全局搜索相结合的粒子群算法。
This paper proposes a particle swarm optimization based on local and global combined search.
第二，提出一种飞行时将自适应调整的粒子群算法。
Second, a modified PSO algorithm with flying time adaptive adjusted is proposed.
然后，运用改进的粒子群算法分派并优化配送线路。
Secondly we propose a modified particle swarm optimization to arrange customers visiting sequences for every vehicle.
说明：这个是详细的粒子群算法代码。大家可以借鉴参考。
This is the detailed particle swarm optimization code. We can learn from the reference.
耗散粒子群算法是一种结合自组织耗散理论的粒子群算法。
Dissipative Particle Swarm Optimization (DPSO) is developed according to the self-organization of dissipative structure.
提出了一个改进的粒子群算法并将其用于解决多目标优化问题。
An improved particle swarm algorithm to solve multi-objective problems is proposed.
我们也建议用混合版本的粒子群算法嵌入局部优化，提高了性能。
We also propose to use a hybrid version of PSO embedding a local optimizer to enhance the performance.
实验结果表明该算法优于几种典型的粒子群算法和基本免疫克隆算法。
The experiment results demonstrate that the proposed algorithm is superior to several typical modified PSO algorithms and immune clone algorithm.
提出一种新的粒子群算法(PSO)边界变异策略——最小值边界变异。
A new boundary mutation strategy, the minimum boundary mutation, is presented based on Particle Swarm Optimization (PSO).
实验结果表明，改进后的粒子群算法防止陷入局部最优的能力有了明显的增强。
The experimental result indicates that the modified PSO increases the ability to break away from the local optimum.
结果表明，改进的粒子群算法具有改善早熟现象的优点，且预测效果有所提高。
The results show that the improved PSO has the advantages of improving premature and the prediction effect is raised.
基于收缩因子改进的粒子群算法可以保证算法的收敛性，同时使得速度的限制放松。
The improved particle swarm algorithm based on constriction factors can guarantee the constringency of the algorithm, while the restriction of velocity can be released.
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.
实验证明采用这种改进的粒子群算法解决多约束背包问题切实可行， 搜索效率较高。
The result of this experiment shows that this particle swarm algorithm is available and efficient in solving multi-c…
本文在阅读了大量有关粒子群算法的文献的基础上，对标准的粒子群算法研究和分析。
In this paper, consulted a lot of literature about particle swarm optimization algorithm, and did research and analysis on the standard particle swarm optimization.
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。
In this paper, a modified particle swarm optimization algorithm is presented to solve knapsack problem, and the detailed realization of the algorithm is illustrated.
在标准粒子群算法的基础上，针对关键参数经验设置法的局限性，提出了一种新的粒子群算法。
Based on the standard particle swarm optimization algorithm, a new algorithm using uniform design to determining parameters is presented in this paper.
建立了集合划分问题的优化数学模型，结合遗传算法的思想提出的粒子群算法来解决集合划分问题。
This paper shows us a study of the division and combination problem of DE on the basis of division and combination history along with a division and combination perspective.
且改进的粒子群算法在模糊神经网络权值的训练中收敛速度和跳出局部最优的能力都要比BP算法更优。
And, in FNN weight training, improved PSO in the convergence rate and the ability to jump out to local optimum algorithm is better than BP.
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)。
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.
仿真结果表明：改进后的粒子群算法迭代次数少，收敛速度比改进的BP算法快，可以对变压器的故障类型进行区分。
Simulation results show that the iterations are fewer, convergence rate is faster than the improved BP algorithm, and the transformer fault types can be distinguished.
简要介绍了基于模拟退火思想的粒子群算法的基本原理，并将之应用于盲源分离算法中，以解决基本粒子群算法收敛速度缓慢的问题。
The basic principal of particle swarm optimization based on simulate anneal was introduced and was applied to blind source separation to solve the problem of low searching speed.
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.
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.
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