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.
将改进粒子群优化算法应用于三维空间路径规划。
The improved particle swarm optimization algorithm is applied to path planning problem in 3-D space.
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.
由冶金准则及设备约束条件设计优化算法的价值函数，用改进粒子群优化算法以价值函数值最小化为目标，对二冷区各段的水量进行优化。
Value function consists of metallurgical criteria and equipment constraints, the IPSO algorithm applies for optimal of the secondary cooling system aiming at minimize value function.
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.
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.
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.
在求解冷负荷启动中的配电网馈线供电恢复问题时引入了离散粒子群优化算法并对该算法进行了改进。
Here, discrete particle swam optimization algorithm is introduced to solve the problem of optimal restoration of distribution feeders during cold load pickup.
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.
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.
并对普通粒子群优化算法进行了改进，提高了优化过程的求解精度和收敛速度。
Furthermore, PSO was modified here to improve the solving precision and convergent rates of optimization procedure.
计算实例表明改进型粒子群优化算法大大改善了传统PSO算法的全局收敛性能，解的精度提高了很多。
The results show that IPSO can improve the global convergence performance of traditional PSO greatly, heighten the accuracy of the solution.
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.
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.
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.
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.
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.
应用改进的粒子群优化算法优化PID参数。
The improved particle swarm optimization (PSO) is used to optimize the PID controller parameters.
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.
然后，运用改进的粒子群算法分派并优化配送线路。
Secondly we propose a modified particle swarm optimization to arrange customers visiting sequences for every vehicle.
通过应用实例证明，将改进的粒子群优化算法应用到电力负荷组合预测模型的权重求解是可行的。
Application examples show that it is feasible to apply the improved PSO to the weight solution of power load combination forecasting model.
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.
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.
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