查询词典 optimization problem

Through this model, which could make full use of the given prior information as the constraints of maximum likelihood estimation and based on Lagrange function, the calculation problem of fault prior probabilities was transformed to non-constrained optimization problem.

该模型以相关的先验信息作为最大概率估计的约束条件，并通过拉格朗日函数，将故障先验概率估算问题转化成无约束优化问题。

In this paper, we start with a new formulation which is proposed based on the K-SVCR method. We then transform it as a complementarity problem and further a strongly convex unconstrained optimization problem by using the implicit Lagrangian function.

在本文中，我们首先在K-SVCR方法的基础上提出了新的模型，然后把新模型转化成一个互补问题，并利用Lagrangian隐函数进一步转化成一个强凸的无约束优化问题。

Furthermore, the design problem of the suboptimal guaranteed cost controller is turned into a convex optimization problem with linear matrix inequalities constraints.

在此基础上，将次优保性能控制器设计问题转化为一组线性矩阵不等式约束下的凸优化问题。

Based on the proposed performance criterion, a sufficient condition for the existence of gain-scheduled H2/H(subscript ∞) filter is derived. Furthermore, the filter design problem is converted into a convex optimization problem with linear matrix inequality constraints.

基于该性能准则，推导了变增益H2/H滤波器存在的充分条件，并将滤波器设计问题转化为具有线性矩阵不等式约束的凸优化问题。

To reduce the conservatism in the estimation, the Schur complements of the matrixes are applied to transform the problem of selecting a suitable quadratic Lyapunov function into a simple convex optimization problem with linear matrix inequality constraints.

同时为了减少保守性，利用矩阵的Schur补性质，将如何选取该二次型Lyapunov函数的问题转化为标准的LMI凸优化问题。

To distribution center, vehicle routing problem is a pivotal problem to logistic system optimization.

对配送中心来说，物流配送车辆的路径优化是物流系统优化的一个关键环节。

Since the stability of the neural network don't require the convexity of the original maximin problem, the obtained results can be applied to solve a class of nonconvex optimization problem.

由于稳定性分析中不需要原极大极小问题的凸性，该网络可以用来求解一类非凸优化问题。

In order to study vector-valued optimization problem, in chapter 5, a class of vector -valued function, that is, uniformly same-order set-valued function is introduced , which includes the separated functions as its proper subset; without hypothesis of convexity, new minimax theorem and saddle point theorem for uniformly same-order set-valued function are established. Next, by employing Ky Fan\'s lemma and H-KKM mapping , several existence results for generalized vector equilibrium problem established.

为了研究向量优化问题，作为可分函数的推广，第五章引入了一致同阶集值函数类，在没有凸性条件的假设下，对一致同阶集值函数建立了新的极小极大定理与鞍点存在定理；利用H-KKM映射，对一般向量均衡问题建立了(来源：A73BcbC论文网www.abclunwen.com)几个存在性定理；最后讨论了集值向量均衡问题系统，利用集值映射的拟凸性，在较弱的条件下证明了解的存在性。

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。

It elaborates the multistage dynamic programming model of section decisive process optimization problem, and usually the essential f actor that contained. It be given two prerequisites of problem that may solve with dynamic programming" the optimum son-structure with no rear effect ".

阐述了一个多阶段决策过程最优化问题的动态规划模型通常包含的要素，给出了一个用"动态规划"可以解决问题的两个先决条件："最优子结构"与"无后效性"。

Now he worked in ajoint venture.

现在他在一家合资企业工作。

More troops in Afghanistan won't change any of the foregoing.

更多的在阿富汗的军队也不会改变之前的状况。