提出了基于改进的二进制粒子群优化算法、以均衡负荷为目标的配电网重构方法。
A method based on improved binary particle swarm optimization (PSO) is proposed for distribution network reconfiguration with the objective of load balancing.
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.
提出了一种新的改进的粒子群优化算法，并以水轮机转速偏差的加权ITAE指标作为改进粒子群优化算法的适应度函数。
An improved particle swarm optimization (PSO) algorithm was designed. And a weighted ITAE index of turbine speed error was taken as the fitness function of the improved PSO algorithm.
针对不同的网络实际条件，提出一种改进的离散粒子群算法来寻找网络中任意两个节点间的最优路由。
In this paper, a new routing approach based on discrete particle swarm optimization algorithm is briefly discussed to obtain the optimum path between two nodes in the network.
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.
针对动态自标定的问题，提出了一种改进的基于粒子群优化(PSO)的自标定位置视觉定位算法。
In allusion to the problem of dynamic self-calibration, a novel self-calibrating algorithm for visual position based on particle swarm optimization (PSO) is suggested in this paper.
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.
在此基础上，进一步提出了混合粒子群算法和速度变异粒子群算法两种改进算法提高优化性能。
For improving the predicting results, two improved PSO algorithm are presented also in this paper: Velocity Mutation PSO and hybrid PSO.
本文提出一种基于改进粒子群算法的P 2 P流媒体数据调度方法。
This paper presents an improved particle swarm optimization algorithm based on P2P streaming media data scheduling method.
提出了一种基于带有变异算子的改进粒子群算法对二冷区水量进行优化的新方法。
A novel method based on modified particle swarm optimization (IPSO) with mutation algorithm was proposed to optimize water quantity in secondary cooling process in the continuous slab casting.
提出了改进的粒子群优化算法。
In this paper, a modified particle swarm optimization method is proposed.
在此基础上，提出基于改进粒子群算法优化的磁轴承神经网络PID控制方案。
On this basis, improved particle swarm optimization based on the magnetic bearing neural network PID control scheme is proposed.
提出了一种非对称互联型粒子群算法（AFIPSO），它是对互联型粒子群算法的改进。
A new algorithm, called Asymmetric Fully Informed Particle Swarm Optimization(AFIPSO), is given.
该文探讨了粒子群优化算法及其改进，并提出了算法的离线性能评估准则和在线性能评估准则。
This paper discussed the particle swarm optimization (PSO) and its improvement. The online performance and offline performance evaluation of PSO is also provided.
本文提出了用于求解单级多资源约束的生产批量计划问题的改进二进制粒子群算法，阐明了算法的具体实现过程。
In this paper, the improved particle swarm optimization algorithm for the single level capacitated dynamic lot-sizing problem is presented. The detailed realization of the algorithm is illustrated.
为了克服粒子群算法在求解多峰函数时极易陷入局部最优解的缺陷，提出一种基于自适应动态邻居广义学习的改进粒子群算法(ADPSO)。
As Particle Swarm Optimization (PSO) may easily get trapped in a local optimum, an improved PSO based on adaptive dynamic neighborhood and comprehensive learning named ADPSO was proposed.
为了解决常用的状态估计方法常易出现的发散现象，提出了基于改进粒子群算法的状态估计。
In order to solve the divergence phenomenon which produced by the common state estimation methods, a state estimation method based on improved particle swarm algorithm was proposed.
为了增强情感识别过程中皮肤电反应(GSR)信号特征选择的有效性，提出了一种改进的模拟退火免疫粒子群算法。
An improved immune particle swarm optimization was presented in this study in order to increase the effectiveness of feature selection for emotion recognition based on Galvanic Skin Response (GSR).
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.
文中提出了一种基于改进离散粒子群优化算法求解机组组合问题的新方法。
A solution to unit commitment via an enhanced binary particle swarm optimization (BPSO) algorithm is presented.
本文提出一种精确的多目标优化算法，即改进的双群体差分多层文化粒子群融合算法。
The paper put forward a kind of accurate multi-objective optimization-double populations differential multi-storey culture particle swarm fusion arithmetic after improving.
针对协同粒子群优化算法存在的停滞现象，提出了一种改进的协同粒子群优化算法。
Aiming at the stagnation problem of the cooperative particle swarm optimization, this paper presents an improved cooperative particle swarm optimization.
针对粒子群算法本身存在早熟的不足，提出了一种改进的粒子群优化算法(IPSO)。
Aimed at PSO's defect of prematurity, an improved particle swarm optimization (IPSO) is presented.
提出了基于场景的多目标随机规划模型来构建不确定市场需求环境下的能力计划问题模型，并用改进的多目标粒子群优化算法求解。
We formulated scenario based multi-objective stochastic programming model to describe the problem of capacity planning under uncertainty and applied improved Multi-Objective PSO (MOPSO) to solve it.
根据限流措施优化配置问题的特点，提出先对候选可开断支路采用枚举法求解支路开断的优化方案，再采用改进离散粒子群算法(MDPSO)求解综合限流方案。
An enumeration method was used to get the optimal splitting of the candidate branches. A modified discrete particle swarm optimization algorithm (MDPSO) was used to get the final strategy.
为了提高粒子群算法的寻优速度和寻优精度，提出一种改进的PSO混合算法。
This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm.
为了提高粒子群算法的寻优速度和寻优精度，提出一种改进的PSO混合算法。
This paper proposed a novel Particle Swarm Optimization (PSO) hybrid algorithm to improve the optimum speed and performance of the PSO algorithm.
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