convex programming造句
例句与造句
- The convergence of an algorithm for the reverse convex programming
一类反凸规划算法的收敛性 - The affine scaling algorithm for convex programming with linear constraints
线性约束凸规划问题的仿尺度算法 - Convex programming problem
凸规划问题 - Solving linearly constrained convex programming by potential reduction interior - point algorithm
求解线性约束凸规划的势下降内点算法 - Finally , the relationships between generalized set - valued variational inclusion problems and non - convex programming are studied
最后研究了广义集值变分包含问题与非凸规划之间的关系。 - It's difficult to find convex programming in a sentence. 用convex programming造句挺难的
- Fifthly , the parameter control methods for solving convex programming , especially linear programming and convex quadratic programming , are discussed and its convergence iv is probed
五是研究了凸规划包括线性规划和凸二次规划的参数控制算法及其收敛性。 - Abstract : this paper presents a new primal ? dual interior point algorithm for a convex programming with box constraints , and prove the iteration complexity is polynomial
文摘:本文为框式约束的一类凸规划提出了一个新的内点算法，原始-对偶路径跟踪法，并证明了算法的迭代复杂性为多项式时间性 - The mathematical programming methods , both the method of moving asymptotes ( mma ) belonging to convex programming methods and the sequential linear programming method ( slp ) , were used to solving optimization problems
用移动渐进线方法( mma )求解单目标优化问题，用序列线性规划方法( slp )求解模糊目标混合规划问题。 - Finally , prove that any global optimal solution of the converted concave minimization problem or reverse convex programming problem obtained by the existing algorithms is an approximate global optimal solution of the original problem
最后，还证明了得到的凹规划和反凸规划的全局最优解就是原问题的近似全局最优解。 - Abstract : an algorithm of indefinite quadratic programming over unbound domain is presented ; the indefi nite quadratic programming is translated into a series of convex programming and the convergence of algorithm is discussed
文摘:给出了无界域上不定二次规划的一个算法，该算法将不定二次规划转化为一系列凸二次规划，并证明了算法的收敛性 - The generalized support vector machines ( gsvms ) was proposed by mangasarian , but it can not be degenerated to the standard svms . in fact , the former only consider the strict convex programming , while the latter considers the convex programming
Mangasarian提出广义支持向量机，但不包含标准的支持向量机：前者研究一般的严格凸规划问题，而后者针对的是特定的凸规划问题。 - At the beginning of their research , they could transform some nonlinear programming into relevant dual , such transformation made some outcome almost similar to linear programming . but if they wanted meaningful results , they had to consider convex programming
在初期，他们发现可以将某些非线性规划表述为一个相应的对偶规划，且有少量相似于线性规划的结果，但如果希望得到有意义的结果，只能考虑凸规划。 - The paper discusses convex programs with an additional reverse convex constraint and gives the properties of the global optimization about this problem . a branch - and - bound algorithm for solving this problem is constructed and the convergence properties of this algorithm is analysed
讨论带一个反凸约束的凸规划问题.给出了整体最优解的特性，利用此特性借助分枝定界方法，构造出求该问题整体最优解的算法，并进行了收敛性分析 - In the progress of deducing the dual of these two problems using the knowledge of convex programming and generalized fenchel theory , you can find lagrange dual of the two programming by lagrange dual in nonlinear programming in this article
基于凸规划知识和广义的fenchel定理，作者推导出这两类问题的凸对偶规划。同时，发现由非线性规划中lagrange对偶可以获得这两类问题的lagrange对偶规划，且推导过程中没有涉及很深的数学知识，使得应用更为广泛。 - This paper consists of three parts as follows , 1 . a nonsmooth convex programming is relaxed to a smooth convex programming by using a cutting - plane , which is constructed by subgradient . an algorithm based on the cutting - plane is presented . in this way , a cutting plane algorithm and it ' s convergence for semide ? nite programming are provided
利用次微分的概念给出了一种非光滑凸规划割平面的构造技巧，找到了半定规划可行域的一个支撑超平面，从而给出了求解半定规划的一种割平面算法
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