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- Study on Function Optimization and Model Reduction Based on a Class of Hybrid PSO Algorithm 基于一类混合PSO算法的函数优化与模型降阶研究
- A Hybrid PSO Algorithm for Flow Shop Scheduling Problem with Earliness/Tardiness 基于提前/滞后Flow Shop调度问题的混合微粒群算法
- hybrid PSO algorithm 混合粒子群算法
- It is supposed that the hybrid PSO will be an effective method for discrete combinatory problems. 该算法是一种求解离散组合优化问题的有效方法。
- An improved PSO algorithm was presented and applied to optimal the PID parameters of electromotor. 为此,提出一种改进的PSO优化算法,并将该算法应用于电机控制系统的PID参数优化设计。
- It is showed that the PSO algorithm is an efficient method to deal with NLP problems. 结果表明 ,PSO算法在使用的普遍性、求解的准确性方面都优于一般的算法 ,是一种有效的求解NLP问题的方法
- At last, applications of PSO algorithm are discussed, and further research issues and some suggestions are given. 最后归纳了PSO算法的应用概况，并就PSO算法进一步的研究工作进行了探讨和展望。
- The PSO algorithm is improved to make it more intelligent, which is used in mute planning of the cruise missile. 对近年来出现的粒子群算法进行了改进以使其更具智能化，将它应用于巡航导弹路径规划问题，并进行了仿真计算。
- The experimental results show that the PSO algorithm provides an effective method to estimate parameters of NSM. 实验结果表明：微粒群算法为非线性系统模型参数估计提供了一种有效的途径。
- The results of simulation show that the proposed PSO algorithm has its high validity, robustness and efficiency. 仿真结果表明，改进的PSO算法有更好的搜索效率，取得了较好的效果。
- Traditional analog filter is imprecise and inefficient, The optimal parameters of the filters can be obtained by introducing the PSO algorithm. 传统的模拟滤波器的精度与效率均较差，引入PSO算法可对滤波器参数进行寻优。
- Some illustrating results show that the PSO algorithm is usable and valid for both structural model updating and structural damage detection. 由此可见，PSO算法应用于该领域的效果是显而易见的。
- If some particles trended to local extremum in PSO algorithm implementation, the particle velocity was updated and re-initialized. 在PSO算法的运行过程中，对有集聚倾向的粒子进行速度变异处理，重新初始化速度。
- The adoption of niche concept improves the ability of PSO algorithm in solving multimodel function optimization problems. 小生境技术的引入,提高了微粒群算法处理多峰函数优化问题的能力。
- A novel two-swarm based PSO algorithm (TSPSO) with roulette wheel selection was proposed to solve optimal power flow problem. 提出一种带赌轮选择的双种群粒子群优化算法(TSPSO)求解最优潮流问题。
- To get better optimization results, an improved PSO algorithm named IPSO including variance mechanism and local updating mechanism was presented. 为提高其优化求解效果，引入变异机制及局部更新机制对粒子群优化算法进行改进。
- PSO is simple and easy to implement, but the value of inertia parameter and the swarm size have an important effect on the PSO algorithm performance. 摘要PSO的优点是算法表达简单，易于实现，其中的惯性权重参数选择和种群大小选择对算法特性有显著影响。
- Abstract: A novel two-swarm based PSO algorithm (TSPSO) with roulette wheel selection was proposed to solve optimal power flow problem. 摘 要： 提出一种带赌轮选择的双种群粒子群优化算法(TSPSO)求解最优潮流问题。
- An improved fuzzy adaptive PID algorithm (IFPID) is thus proposed, using PSO algorithm to optimize the preprocessed membership function. 针对这种情况，提出改进的模糊自适应PID控制算法(IFPID)，利用微粒群算法对经过预处理的隶属度函数进行优化。
- The PSO algorithm is a new evolutionary computation method which is applicable to complex optimization problems that are nonlinear, nondifferentiable and multimodal. 微粒群算法是一种新兴的算法,它能有效地解决非线性、不可微、多峰的复杂优化问题。
