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pso算法
    The simulation showes the effectiveness of PSO algorithm in parameter optimization.
    经仿真证明PSO算法参数优化的有效性.
    Rotate surface transformation PSO algorithm for solving (nonlinear) (optimal) control problem
    旋转曲面变换PSO算法解非线性最优控制问题
    Logical layered-and-delayed PSO algorithm and application based on formalization description
    基于形式化描述的逻辑分层延迟PSO算法及应用
    Initialization of the wavelet parameters and the applications of advanced PSO algorithm in WNN
    WNN中的改进PSO算法及参数初始化
    Application of PSO Algorithm with Compression Factor in Gear-box Faults Diagnosis
    带收缩因子的PSO算法在齿轮箱故障诊断中的应用
    A New PSO Algorithm Based on the Statistical Regulation of the Particle Swarm
    基于粒子群统计规律的PSO算法
    Application of PSO Algorithm in Mobile Networks Planning
    PSO算法在通信基站分布规划中的应用
    Application of Modified PSO Algorithm in the Optimization of Reactive Power
    改进PSO算法在无功优化中的应用
    Modified PSO Algorithm for Power System Unit Commitment Optimization
    改进PSO算法解决电力系统机组优化组合问题
    In the system a kind of controller is designed which is the combination of PSO algorithm and PID control theory.
    并将PSO算法与PID控制方法相结合,设计了一种基于PSO算法的PID控制器;
    This scheme expand the application range of neural network and PSO algorithm in
    同时也拓展了神经网络和PSO算法等智能算法在工业控制领域的应用范围,在一定程度上推动了神经网络技术、PSO算法等智能算法的发展。
    To avoid the possible occurring of stagnation phenomenon in the PSO algorithm, the re-initialization mechanism based on the global information feedback is introduced in the MPSO.
    针对PSO算法可能出现的停滞现象,MPSO引入了基于全局信息反馈的重新初始化机制。
    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
    The method utilizes the PSO algorithm to speed up the learning of the neural network, and doesn't have the disadvantages of the BP algorithm such as slow convergence and local minimum.
    与传统反向传播(BP)算法相比,采用PSO算法来训练神经网络,可以有效地克服传统算法收敛速度慢、易陷于局部极小值等缺点,并且训练出的神经网络在泛化能力上也有很大的提高。
    To avoids the local minimum problems and to improve convergent speed, a new probability of PSO algorithm was proposed.
    为了避免PSO算法在求解最优化问题时陷入在局部最优及提高PSO算法的收敛速度,提出了对PSO算法增加更新概率。
    The experiments show that the PSO algorithm is simple and the accuracy of the curve obtained by PSO algorithm is high.
    实验研究表明:PSO算法简单、得到的传感器非线性校正曲线精度高。
    The mean fitness value obtained by using NPSO is about from 1.62% to 16.5% highter than that obtained by using pso algorithm under given conditions.
    实验结果显示,在获得平均适应值方面,该算法比PSO算法提高1.62%~16.5%,明显优于基本的PSO算法
    Using the PSO algorithm to optimize the on-line PID controller's parameters, desirable control effect is obtained.
    通过运用PSO算法对PID控制器参数进行在线调整,使模型参考自适应控制达到理想的控制效果。
    By the use of extended PSO algorithm of hybrid tactics in GA,the function of PSO algorithm was enhanced.
    利用GA中的杂交策略扩展PSO算法,提高了PSO算法性能。
    Comparison studies between the optimized data obtained by genetic algorithm(GA) and those by PSO algorithm were made.
    同时对遗传算法(GA)和PSO算法优化结果进行对比研究.
 

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