最佳化问题

词组短语

optimalization problem

与最佳化问题相关的网络例句 [注：此内容来源于网络，仅供参考]

This dissertation aims to probe into the warpage of flash memory card connecter, forecast the possible question through CAE analysis, and select the most proper type of gate, and optimize it through the differentiation caused by the molding condition regulation with Taguchi-methods.

本论文的目的是在改善与探讨快闪记忆卡连结器架构之翘曲变形现象，应用CAE模流分析软体预测可能发生的问题，选择出最佳的进浇模式，并利用田口方法探讨不同的成型条件设定所可能产生的差异性，并予以最佳化。

It is a heuristic algorithm that can be used to solve discrete optimization problems.

模拟退火法的构想源於金属冷却结晶的过程，是一种常用於求解最佳化问题的启发式演算法。

For solving this nonideal problem, the orthogonality between the directional vector and the noise subspace with the same frequency can be used to establish a cost function. After finding the appropriate solution with the minimum cost function value through different optimization methods, the LCMV algorithm can use the result to calculate the optimum weight.

为了解决这项在波束成型上的非理想问题，我们利用了宽频信号的方向向量会和同频率的杂讯子空间正交的特性[4，5]去建立一个目标函数，利用不同的最佳化方法找出适当的解，再带入LCMV演算法中算出最佳权重。

The problem of multi-objective usually meet many conflict each other and can not use the objective of the same standard unit, then to employ membership function of fuzzy theory,at first each objective function to change fuzzy set and express with membership function, membership function include the maximum constraint, minimum constraint, the decrease function of monotonic property, to become optimal of the multi-objective function, but still to scanty of weighting value with regard to adjustment of objective function, thus this thesis proposes the method of combine orthogonal arrays and particle swarm optimization to solve the problem of multi-objective optimal power flow, each objective function separately add weighting value, to setting each weighting value of objective function in order to the result of anticipating.

多目标最佳化的问题通常会面临到许多互相冲突且不能用同ㄧ标准单位的目标，於是利用模糊理论中的归属函数，首先将各目标函数转换成模糊集合并以归属函数表示，归属函数包含了最大限制值、最小限制值、单调的递减函数所组成，将各目标函数利用归属函数表示，形成单一目标函数的最佳化，但是仍缺乏权重值对於目标函数的调整，於是本篇论文提出ㄧ种权重值设定与粒子群优演算法的方法去解决多目标最佳电力潮流的问题，将各目标函上分别加上权重值设定各目标函数的权重值，得到预期的效果。

The typical rate allocation mechanism is formulated as a rate-distortion optimization problem and a simple searching method with slow convergence rate is used.

一般典型的流量控制机制可归类为两个重要的过程，一是压缩大小和失真度之间的最佳化问题，另一为简单但收敛速度慢的搜寻方法。

This thesis studies a widely used first order optimzation algorithm--Sequential Linear Programming method, SLP is modify so that it can solve structural and shape optimization problems more efficiently, including continuous and dsicrete variables problems. Finally the zeroth order optimization method is presented for two dimensional shape optimization problems.

本研究将从一般广为设计者所采用的一次最佳化方法--线性序列规划法的修正研究，以使其更稳定且更有效率地解决在一般结构与形态最佳化问题，包含有连续式及非连续式设计变数的最佳化问题演算过程，最后应用零次最佳化方法概念在二维形态最佳化设计上。

The essential effect of feature selection is to improve the accuracy and speed of classification systems. Niched Pareto Genetic Algorithm is a powerful method to solve optimization problems with multiple objectives.

利基柏拉图基因演算法是一种针对多目标最佳化问题所发展出来的工具，可找到多个目标之间的折衷最佳解，以供分析人员选择，而这些折衷最佳解所形成之理想曲线，称为柏拉图最佳边际。

The solution of the heat balance equation for gas-cooled current leads is presented.

给出了在气冷引线最佳化问题中求解热平衡方程的方法。

Reducing the overkills and retests in a wafer testing process can be formulated as a stochastic simulation optimization problem with huge decision-variable space . For this problem, we have proposed an ordinal optimization theory based two-level algorithm to solve for a good enough solution.

降低晶圆测试程序中的误宰与重测可以形成一个具有巨大决定变数空间的随机模拟最佳化问题，针对此问题我们提出一个以序的最佳化方法为基础的两层次演算法，来求解一个足够好的解。

We applied the proposed algorithm to the reduction of overkills and retests in a wafer testing problem, which is formulated as a stochastic simulation optimization problem that consists of a huge decision-variable space formed by the vector of threshold values in the wafer testing process.

我们将所提出的方法应用在降低晶圆测试程序中的误宰与重测问题，这是一个由测试程序中门限值向量所组成，含有巨大决定变数空间的随机模拟最佳化问题。

与最佳化问题相关的网络解释 [注：此内容来源于网络，仅供参考]

combinatorial optimization problem：组合的最佳化问题

组合逻辑 combinatorial logic | 组合的最佳化问题 combinatorial optimization problem | 组合的程序设计 combinatorial programming

discrete optimization problem：离散最优化问题

discrete optimization 离散最佳化 | discrete optimization problem 离散最优化问题 | discrete problem 离散问题

discrete optimization：离散最佳化

discrete mathematics 离散数学 | discrete optimization 离散最佳化 | discrete optimization problem 离散最优化问题

objective function：目标函数

在利用GA求解最佳化问题前,需先决定目标函数(objective function)、设计变数(Design variables)和搜寻空间. 接著将设计变数编码成类似生物染色体的字串,字串中的各个位元相当於基因(Gene),

optimalization problem：最佳化问题

optimality principle 最优性原理 | optimalization problem 最佳化问题 | optimization 最佳化

optimization problem：最佳化问题

.以演算法中三大基本指令,序列性(Sequence),重覆性(Iteration),递回性(Recursive)为中心,分析每一步骤所须的处理时间与空间,分析演算法的优劣.贪婪策略(Greedy Method)常用来解决最佳化问题(Optimization Problem).贪婪法是最直接的解法,

optimization：最佳化

进化计算以观察自然界生物与生命现象之动态变化为想法出发,开发符合自然状态之进化模拟演算法,可应用於搜寻 (Search)、设计 (Design)、与最佳化 (Optimization) 等各类问题解决之演算方法或解题技术,可应用的范围非常广泛.

Processed：加工

1.待加工(Processed)的工作及作业(Operation)数2.现场(Shop)的机器数目和种类禁忌搜寻法(tabu search)为Glover於1977年提出,是一种高阶的万用启发方法,用於解决组合最佳化问题,

Optimization Toolbox：(最佳化工具箱)

取得网路服务(Web services)能支援MathWorks job manager或外部电脑调度程式(schedulers)针对medium-scale问题,提供无限制条件下求函数最小值之最佳化函式(fminunc)简介 最佳化工具箱(Optimization Toolbox)提供了经过验证的一般最佳化和大规模最佳化演算法,

wiring：配线

有些求解的方法结合它和遗传演算法(genetic algorithm)的优点. 它也和类神经网路有某些程度的相似. Kirkpatrick等(1993)利用模拟退火法来求解定位(Placement)、电路配线(Wiring)及销售员旅途问题(Traveling Salesman)等组合最佳化问题上.