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- standard PSO algorithm 标准粒子群算法
- Two VRP examples are solved by this algorithm, and the results are compared with those by both genetic algorithm (GA) and standard PSO. 用该算法求解了两个车辆路径问题的算例,并与遗传算法和标准粒子群算法进行了比较。
- In order to overcome the shortcomings that standard Particle Swarm Optimization(PSO) traps into local optima easily and has a low convergence accuracy,an improved PSO algorithm is proposed. 摘要 针对标准粒子群算法容易陷入局部最优、收敛精度低的缺点,提出了一种改进的粒子群算法。
- Finally,the performance of NQPSO algorithm is compared with those of Standard PSO(SPSO) and original QPSO by testing the algorithms on several benchmark functions. 并用若干个标准函数进行测试,比较了NQPSO算法与标准PSO(SPSO)和传统QPSO算法的性能。
- Finally,the performance of AQPSO algorithm is compared with those of Standard PSO(SPSO) and original QPSO by testing the algorithms on several benchmark functions. 最后,用若干个标准函数进行测试,比较了AQPSO算法与标准PSO(SPSO)和传统QPSO算法的性能。
- 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
- Niche chaotic mutation particle swarm optimization (NCPSO) is proposed to overcome the problem of the premature and low precision of the standard PSO. 摘要针对粒子群算法早熟收敛和搜索精度低的问题,提出了基于混沌变异的小生境粒子群算法(NCPSO)。
- 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。
- An improved particle swarm optimization (PSO) with disturbance (DPSO) was put forward to enhance the performance of PSO by introducing an evolution speed factor in standard PSO. 通过对故障电压波形的逻辑预处理得出12维故障向量及相应的故障编码。
- 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。