本文采用改进粒子群算法求解货物装载问题。
In this paper, a particle swarm algorithm was presented to solve the Freighting problem.
应用改进粒子群算法求解梯级水电站短期优化调度问题。
Improved Particle Swarm Optimization is applied to short-term optimal scheduling of the cascade hydropower plants.
利用改进粒子群算法替代BP算法优化神经网络的权值系数。
Alternative use of improved particle swarm optimization neural network BP algorithm weight value.
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.
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.
在隐空间中支持向量机求解过程中，引入改进粒子群算法用于搜索空间的迭代。
During the solving course of hidden space support vector machine, this paper introduces the Particle Swarm Optimize Algorithms.
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.
最后，本文对于改进粒子群算法的应用前景进行了展望，并给出了进一步的研究方向。
At last, the thesis predicts the application prospect of the improved particle swarm optimization and gives some directions of future research.
标准测试函数的特性与选择，改进粒子群算法与标准粒子群算法的比较实验与结果分析；
The features and options of Standard test functions, The comparative experiment and the results analyzing of the improved standard particle swarm algorithm and particle swarm optimization ;
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.
其次，采用一种基于改进粒子群算法的路径规划方法实现了飞行机器人的全局路径规划方法。
Secondly, the improved particle swarm optimization for flying robot for overhead powerline inspection is used to resolve the global path planning issue.
为此，根据企业利润最大化原则建立机组经济运行数学模型，并用改进粒子群算法对模型优化求解。
In this paper, based on the principle of maximum profit, a mathematical model of unit which is unit economy operation is presented.
结果表明基于改进粒子群算法的状态估计可以得到最优值，但时间较长，检测法可以检测出不良数据。
The results show that the state estimation method based on improved particle swarm algorithm can be the best value, but a longer time, and the bad data can be detected by J(x) detection method.
采用改进粒子群算法对孤岛运行模式下的一个小型的微网系统算例进行研究，仿真计算结果表明了所提方法的有效性。
The economic dispatch of a small microgird example in island mode was optimized by improved particle swarm optimization PSO method, simulation results show the effectiveness of the proposed method.
第二，将本文所提改进粒子群算法应用于工业PID控制器的参数整定，以及带约束优化的工业设计中，均取得了非常理想的效果。
Secondly, this algorithm is applied to the PID controller tuning and the industrial design with restrictions. The results are fairly well.
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.
求解机组组合问题的嵌入贪婪搜索机制的改进粒子群优化算法。
An improved particle swarm optimization algorithm embedded with greedy search for solution of unit commitment.
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.
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.
改进的粒子群优化算法全局搜索BP神经网络的权值和阈值。
The parameters and thresholds of classifiers are optimized by improved Particle Swarm Optimization(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.
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.
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.
基于收缩因子改进的粒子群算法可以保证算法的收敛性，同时使得速度的限制放松。
The improved particle swarm algorithm based on constriction factors can guarantee the constringency of the algorithm, while the restriction of velocity can be released.
针对此模型，采用改进粒子群优化算法进行求解。
The proposed model is solved by improved particle swarm optimization (PSO) algorithm.
提出了改进的粒子群优化算法。
In this paper, a modified particle swarm optimization method is proposed.
提出了改进的粒子群优化算法。
In this paper, a modified particle swarm optimization method is proposed.
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