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improved pso algorithm
相关语句
  改进的pso
     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。
短句来源
     Neural Network Ensembles Based on Improved PSO Algorithm
     基于改进的PSO算法的神经网络集成
短句来源
     An improved PSO algorithm was presented and applied to optimal the PID gains tuning of hydraulic turbogenerators speed governor. The ITAE criterion of hydraulic turbogenerators speed errors was taken as the fitness function of the improved PSO algorithm.
     文中提出一种改进的PSO优化算法,并将该算法应用于水轮发电机组PID调速器参数的优化设计,以水轮发电机组转速偏差的ITAE指标作为改进PSO优化算法的适应度函数。
短句来源
     But the standard PSO can't lead to convergence of global optimization. In this paper, the improved PSO algorithm, called stochastic PSO, is used to guarantee converge to the global solution for parameter optimization of PID controller.
     但基本微粒群算法不能保证全局收敛,本文将改进的PSO算法(SPSO)应用于PID控制器的参数优化.
短句来源
  改进pso算法
     PSO(Particle Swarm Optimization) algorithm is introduced, and an improved PSO algorithm is proposed for the optimization of short-term generation scheduling . The discrete variables representing the unit status are transformed to continuous variables from zero to one, which together with unit output, are optimized by PSO and finally transformed to integral variables using function'round'.
     介绍了粒子群优化算法PSO(Particle Swarm Optimization),并针对短期发电计划中的优化问题提出了一种改进PSO算法,将表示机组开停机状态的离散变量转换为0~1范围内的连续变量,与机组出力一起进行PSO优化搜索,然后再利用就近取整函数“round”将其转换成整数变量。
短句来源
  “improved pso algorithm”译为未确定词的双语例句
     PID Parameters Optimization for Motor Controller System Based on Improved PSO Algorithm
     基于改进PSO算法的电机控制系统PID参数优化
短句来源
     STRUCTURAL DAMAGE DETECTION BASED ON AN IMPROVED PSO ALGORITHM
     基于改进PSO算法的结构损伤检测
短句来源
     A Study of Application of An Improved PSO Algorithm in BP Network
     一种改进的粒子群算法在BP网络中的应用研究
短句来源
     Improved PSO Algorithm Study and Its Application on Network Routing
     改进粒子群算法研究及其在网络路由中的应用
短句来源
     PID parameters tuning based on improved PSO algorithm
     基于改进粒子群优化算法的PID参数整定
短句来源
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  相似匹配句对
     It has been improved.
     并在应用中不断的改进、完善。
短句来源
     is improved.
     改进了张的相应结果。
短句来源
     Application of Improved PSO for Customization System
     改进粒子群优化算法在个性化定制系统中的应用
短句来源
     Application of Improved PSO in Control of Ferment Process
     改进粒子群算法在酶发酵过程优化控制中的应用
短句来源
     Neural Network Ensembles Based on Improved PSO Algorithm
     基于改进的PSO算法的神经网络集成
短句来源
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  improved pso algorithm
Based on the singularly perturbed description of a flexible robot dynamics, a performance index for trajectory planning with vibration reduction is proposed and is implemented by an improved PSO algorithm.
      


An improved PSO algorithm based on Bootstrap named with BPSO for neural network ensembles is proposed. On the one side, the effect of collinearity is decreased by restricting the range of combination weights. On the other hand, different fitness functions are constructed on different data by using bootstrap technique, which increases the diversity of particles. In consequence combination weights are easier to be adjusted in a definite range and the effects of noise are decreased. Experiments results show...

An improved PSO algorithm based on Bootstrap named with BPSO for neural network ensembles is proposed. On the one side, the effect of collinearity is decreased by restricting the range of combination weights. On the other hand, different fitness functions are constructed on different data by using bootstrap technique, which increases the diversity of particles. In consequence combination weights are easier to be adjusted in a definite range and the effects of noise are decreased. Experiments results show that the BPSO algorithm is an effect ensemble method and improves the generalization ability of neural network ensembles.

提出了一种新的神经网络集成结论生成方法,即基于可重复采样技术(Bootstrap)的粒子群优化(PSO)算法———BPSO算法,通过限制组合权值的范围来减小"多维共线性"的影响,还利用采样技术构造不同的适应度函数,增加"粒子"的多样性从而便于在一定范围内灵活调节组合权值,并减小噪声对集成的影响.实验表明,BPSO算法是优化组合权值的有效方法,提高了神经网络集成的泛化能力.

A particle swarms cooperative optimizer (PSCO) algorithm with two layers framework is proposed. Particle swarms are employed to search best solution in the solution space independently in the bottom layer, and a single swarm is employed in top layer. Sates of the particles of the top swarm are updated based on global best solution has been searched by all the particle swarms both in bottom and top layer. Both the particle numbers of the swarms and updating schemes of particle states are independence. A...

A particle swarms cooperative optimizer (PSCO) algorithm with two layers framework is proposed. Particle swarms are employed to search best solution in the solution space independently in the bottom layer, and a single swarm is employed in top layer. Sates of the particles of the top swarm are updated based on global best solution has been searched by all the particle swarms both in bottom and top layer. Both the particle numbers of the swarms and updating schemes of particle states are independence. A disturbance factor is added to a particle swarm optimizer (PSO) for improving PSO algorithms' performance. When the time of the current global best solution having not been updated is longer than the disturbance factor, the particles' velocities will be reset in order to force swarms getting out of locally minimizers. Three benchmark functions are used in experiments, and the experimental results show that the performances of PSCO are superior to that of classical PSO and fuzzy PSO and hybrid PSO.

提出一种多粒子群协同优化(PSCO)方法.PSCO是2层结构:底层用多个粒子群相互独立地搜索解空间以扩大搜索范围;上层用1个粒子群追逐当前全局最优解以加快算法收敛.这些粒子群含的粒子数以及粒子状态更新策略不要求相同.为改善粒子群容易陷入局部极小的弱点,提出扰动策略,当1个粒子群的当前全局最优解未更新时间大于扰动因子时,重置粒子的速度,迫使粒子群摆脱局部极小.用Rosenbrock函数等3种基准函数做优化实验表明,PSCO性能优于经典PSO,FPSO和HPSO等算法.

An improved particle swarm optimization (PSO) algorithm to solve the economic dispatch (ED) problem in power system is proposed. In the proposed algorithm the non-linear characteristics, such as ramp constraints of the generating units, output restricted zone and non-smooth cost functions, are considered. The constraints of load equalization are processed by reserving feasible solutions and the ramp constraints as well as output restricted zone constraint are processed by employing adaptive...

An improved particle swarm optimization (PSO) algorithm to solve the economic dispatch (ED) problem in power system is proposed. In the proposed algorithm the non-linear characteristics, such as ramp constraints of the generating units, output restricted zone and non-smooth cost functions, are considered. The constraints of load equalization are processed by reserving feasible solutions and the ramp constraints as well as output restricted zone constraint are processed by employing adaptive penalty function to accelerate the convergence speed of the algorithm, and the prematurity is avoided by reinitializing the inactive particle. Simulation results show that the improved PSO algorithm is an effective approach to solve the economic dispatching.

提出了一种求解电力系统负荷经济分配问题的改进粒子群优化算法。该算法考虑了机组的爬坡约束、出力限制区约束、非光滑费用函数曲线等非线性特性,用保留可行解的方法处理负荷平衡约束条件,用自适应罚函数法处理爬坡和出力限制区约束条件,加快了算法的收敛速度,对不活动粒子的处理使算法避免了“早熟”现象。仿真计算表明,改进粒子群优化算法是一种求解负荷经济分配问题的有效方法。

 
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