全局优化

粒子群优化（PSO：ParticleSwarmoptimization）算法是一种有效的全局优化技术。

PSO ( Particle Swarm Optimization ) is an efficient stochastic global optimization technique .

嵌入式CPU设计中Cache性能的全局优化

The Global Optimization of Cache Performance in Embedded CPU Design

逐步缩小搜索域的全局优化法在微波CAD中的应用

A global optimization method based on step by step reducing search area and it 's application for CAD

差分演化算法（DE）的是在解决连续全局优化问题上有着相当好的表现。

Differential evolution algorithm has pretty well performance in solving this continuous global optimization problem .

基于GA的小卫星星务规划的全局优化算法

Scheduling Small Satellite Mission Based on Genetic Algorithm

另一个是系统层次，即优化Cache索引的全局优化方法。

The other is system level and the paper presents a global method of optimizing Cache index .

VLSI互连线的全局优化算法

A Global Optimization Algorithm for Interconnect Delay of VLSI 's

遗传算法（GeneticAlgorithm）是模拟生物在自然环境中的遗传和进化过程而形成的一种自适应全局优化概率搜索方法，它通过选择、交叉和变异三个过程实现。

Genetic Algorithm which simulates descendiblity and evolution of biologist in nature environment forms a searching method of adapting all-round optimize probability . Genetic has been applied in many fields .

PSO算法已经被证明是一种有效的全局优化方法，并且广泛应用于函数优化，神经网络训练以及模糊系统控制等领域。

PSO has been widely applied in function optimization , neural network training , and fuzzy system control , etc.

求解静态Stackelberg决策问题全局优化方法

A Global Optimization Method for the Linear Static Stackelberg Problem

粒子群优化（ParticleSwarmoptimization）算法是一类启发式随机全局优化技术，是一种基于群智能（SwarmIntelligence）方法的演化计算技术。

Particle swarm optimization ( PSO ) algorithm is a Heuristic stochastic global optimization technique , and also PSO algorithm is an evolutionary computation technique based on swarm intelligence method .

改进后的Tabu算法与遗传算法相比，能够在较短的时间内计算得到全局优化的路由方案。

The improved Tabu search algorithm can work out global optimization route schemes in shorter time than the genetic algorithm .

使用遗传算法（GA）实现对可调参数的全局优化，代替通常设计自适应控制器时对参数调节律的繁琐求取。

Universal optimization for adjustable parameters of fuzzy based function is realized by using GA and finding adjust law of parameters in general designing adaptive controller is replaced .

根据概率原理设计了四种支持QoS的竞争调度算法，并进一步探索了用于提高带宽利用率的局部搜索和全局优化的手段。

Four competition scheduling algorithms have been presented based on the probability principles . Then the local search and global optimization methods to increase the bandwidth utilization has been studied .

本文对符号线性比式和问题（P）提出了一个全局优化算法，这类优化问题广泛应用于工程设计、非线性系统稳定性分析等实际问题中。

In this paper a global optimization algorithm is proposed for a class of linear sum of ratios problem ( P ), which can be generally applied to engineering designs and stability analysis of nonlinear systems , and so on .

组合优化中的NP-hard问题和非线性全局优化问题是优化研究中的难点。

The NP-hard problems and the global optimization problems are two categories of the most challenged subjects in mathematical programming .

给出了求解全局优化问题的连续空间的演化规划，应用Markov过程分析了演化规划，并且证明了该算法的全局收敛性。

An evolutionary programming is given to solve global optimized problems in continuous space . We analyze the algorithm by using Markov process and prove global convergence of the algorithm .

基于Hoek-Brown非线性强度准则的节理岩坡稳定性分析全局优化算法

Global optimization method for jointed rock slope stability analysis based on Hoek-Brown nonlinear strength criterion

针对这一问题，本文应用一扩展Hopfield神经网络&耦合梯度网络，建立了油田电力网无功功率管理的全局优化的数学模型。

To solve this problem , an expanded Hopfield neural network-coupled gradient network is used to construct globally optimizing mathematical model of oilfield power system .

根据吉布斯马尔可夫随机场模型和SAR图像斑点噪声的伽玛分布统计特性，应用模拟退火算法，实现雷达截面的全局优化伪似然估计。

Based on Gibbs-Markov random field model and the Gamma distribution property of SAR image 's speckle noise , global optimal pseudo likelihood estimation of radar cross-section can be achieved with simulated annealing algorithm .

提出了一个全局优化算法（GOA）对RS（255239）解码器中的并行钱氏搜索电路进行面积优化。

A global optimization algorithm ( GOA ) for parallel Chien search circuit in Reed-Solomon ( RS )( 255,239 ) decoder is presented .

利用AVO分析和地震反演相结合的三维多道全局优化地震反演技术和方法进行叠前反演。

Prestack inversion is performed by combining AVO analysis and seismic inversion which are three dimensional , multi traces , and full scale optimized .

为克服这些困难，本文采用新的快速训练算法，同时引入全局优化算法&遗传算法（GA），克服局部极小值。

To get over the demerit of slow training , this thesis presents some new faster training algorithms and introduces global optimization algorithm & genetic algorithm ( GA ) against local minimum problem .

采用PSO全局优化算法训练多层前向神经网络权值，使网络训练误差比BP方法降低了两个数量级，并且收敛速度明显加快。

The global optimization called PSO algorithm is applied to train the weights of neural multi-layer forward neural network , which makes the network training error two orders lower than the method of BP in quantitatively .

研究非线性等式约束全局优化问题，其中目标函数和约束函数为C1类函数。

This paper is concerned with the global optimization problem with nonlinear equality constrain , in which the objective functions and constrained functions are C 1 functions .

该文从更基本的优化思想出发，基于概率论提出了一种新的全局优化算法&统计归纳算法（SIA）。

This paper presents a new global optimization algorithm , the statistic inductive algorithm ( SIA ) based on a more fundamental optimization concept .

介绍了现已成为关键智能计算之一的一种新的全局优化搜索算法&遗传算法，并探讨了在混合H2／H∞最优指标下优化控制设计中的应用。

Genetic algorithm , as a new global optimization searching algorithm which becomes one of vital intelligent computation , is introduced here . The application of this algorithm to mixed H 2 / H ∞ optimization index control design is studieded .

仿真结果表明，快衰落信道下动态LMS算法接近理想性能；慢衰落信道下动态LMS算法和全局优化算法结合应用，可以接近理想性能。

Simulation result shows that dynamical LMS algorithm is close to the optimum in fast fading channel , and the combination of dynamical LMS algorithm and global optimization is close to the optimum in slow fading channel in efficiency .

提出一种基于遗传算法（GA）进行生产调度优化的算法，该算法通过GA、启发式调度以及评价算法的有机结合，在调度效率较高的情况下，实现调度方案的全局优化。

A kind of GA based scheduling algorithm is proposed in this paper . The algorithm can be used to obtain the global optimization of the scheduling plan in efficiency with the versatile combination of normal genetic algorithm , heuristic scheduling , and evaluation algorithm .

然后采用Lagrange乘子法将有约束的极小值问题转化为无约束的极小值问题进行求解，得到PHEV的全局优化控制策略。

Then , the constrained minimum problem is transformed into an unconstrained minimum one , which is solved by using the Lagrange multiplier method , with a global optimization control strategy being obtained .