最优化问题

词组短语

optimalization problem

与最优化问题相关的网络例句 [注：此内容来源于网络，仅供参考]

The convex function develeped so many years that convex functionals are now a class of very universal functionals.The kinetic energy in the classical is the most natural convex function.Others like entropy and so on are convex functions.The economic core is closely connected with the convex function.The western economic core question is the optimized question.The optimized theory has something to do with the convex function and the concave function.

凸函数的发展经年已相当完善其应用非常广泛，在古典力学中的动能，就是最自然直接的凸函数，其他如熵……等均是，连经济学的核心都与之有极密切相关，西方经济学的核心问题是最优化问题，最优化理论又与凸函数与凹函数密切相关。

In chapter 2 we propose a linear equality constraint optimization question , the new algorithm is combined with the new conjugate gradient method(HS-DY conjugate gradient method)and Rosen"s gradient projection method , and has proven it"s convergence under the Wolfe line search.In chapter 3 we have combined a descent algorithm of constraint question with Rosen"s gradient projection, and proposed a linear equality constraint optimization question"s new algorithm, and proposed a combining algorithm about this algorithm, then we have proven their convergence under the Wolfe line search, and has performed the numerical experimentation.

在第三章中我们将无约束问题的一类下降算法与Rosen投影梯度法相结合，将其推广到线性等式约束最优化问题，提出了线性等式约束最优化问题的一类投影下降算法，并提出了基于这类算法的混合算法，在Wolfe线搜索下证明了这两类算法的收敛性，并通过数值试验验证了算法的有效性。

During the investigation, the optimization of infinitesimal information granularity is first solved to determine the low bound of the minimal power, and then the optimization of integer bit is solved, resulting in a fast integer bit-loading algorithm.

首先对无限小信息粒度的最优化问题进行分析，确定最小功率的下界。在此基础上再对整数比特的最优化问题进行求解，由此得到了一种快速的整数比特加载算法。

For special vector optimization problems, namely abstract optimization problems, a generalized multiplier rule of Lagrange is given.

对特殊的向量最优化问题，即抽象最优化问题，给出了一个一般的拉格朗日乘子法则。

This paper studies a completely generalized nonlinear quasi-variation-like inclusions problem in the setting of locally convex topological vector space s and proves the existence its solutions.

似变分不等式和广义拟似变分包含问题是研究非凸最优化问题、非凸和不可微最优化问题的重要工具。在局部凸的拓扑向量空间中研究了完全广义非线性拟似变分包含问题，并证明了其解的存在性

Optimization problem of one-dimensional search, which are widely used in engineering to solve practical design optimization problem.

详细说明：最优化问题的一维搜索，在工程当中应用广泛，解决实际操作设计中的最优化问题。

Based on the statistical learning theory and optimization theory, SVMs have been successfully applied to many fields such as pattern recognition, regression and etc.Training an SVM amounts to solving a convex quadratic programming problem.

它将机器学习问题转化为求解最优化问题，并应用最优化理论构造算法来解决问题，本文主要是从最优化理论和算法的角度对支持向量机中的最优化问题进行研究。

The Lexicographic method has subjective and empirical character,so a weighting coefficient is introduced by considering the importance and proportion of each individual object,the preferable result of every individual object can be confirmed by comparing the degree of similarity between the perfect one and the ecumenic one and the Fuzzy optimization will be perfect.

多目标最优化问题最早的出现[1]，应追溯到1772年，当时franklin就提出了多目标矛盾如何协调的问题。由于多目标优化的特点，只有很少问题具有满足所有目标函数最优化的&最优解&，而大多数情况只有一个折衷意义的&偏好解[&2，3]。

For the posed robust fuzzy optimization model, we first derive its deterministically equivalent form(which is just a nonlinear optimization problem), and then analyze the property of the feasible set of it.

论文摘要：本文考虑了鲁棒最优化问题的不确定参数的模糊性质，从而导出了一种新的最优化问题，本文称之为鲁棒模糊最优化问题。

We successively pose a sampling method for robust fuzzy convex optimization, with the sampled problem being polynomially solvable.

对这类问题，本文导出了其确定性等价最优化问题，分析了其可行集的性质，接着对鲁棒模糊凸最优化问题给出了一种样本方法。

与最优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：组合最优化问题

combinatorial method 组合方法 | combinatorial optimization problem 组合最优化问题 | combinatorial path 组合道路

combinatorial problem：组合最优化问题

combinatorial path 组合道路 | combinatorial problem 组合最优化问题 | combinatorial sphere 组合球面

constrained optimization problem：约束最优化问题

约束优化:constrained optimization | 约束最优化问题:constrained optimization problem | 非线性约束优化:nonlinear constrained optimization

constrained optimization problems：约束最优化问题

约束最忧化:Constrained Optimization Problem | 约束最优化问题:constrained optimization problems | 等式约束问题:equality constrained optimization problem

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 problem：离散型最优化问题

discrete material | 松散材料,粒状材料 | discrete optimization problem | 离散型最优化问题 | discrete ordinates method | 离散坐标方法

free optimization problem：自由最优化问题

free monoid 自由独异点 | free optimization problem 自由最优化问题 | free product 自由积

linear optimization problem：线性最优化问题

linear optimization 线性最优化 | linear optimization problem 线性最优化问题 | linear order 线性有序类

optimization problem：最优化问题

本章及后续章节中的许多例子都是最优化问题(optimization problem),每个最优化问题都包含一组限制条件(constraint)和一个优化函数(optimization function),符合限制条件的问题求解方案称为可行解( feasible solution),

unconstrained optimization problem：约束最优化问题

无约束最优化:Unconstrained Optimization Problem | 约束最优化问题:Unconstrained Optimization Problem | 词人之词:Ci-poetey written by ci-poem