二次规划

逐次二次规划法（Sequentialquadraticprogramming，SQP）是目前求解非线性约束问题十分有效的方法。

Sequential Quadratic Programming ( SQP ) is the most efficient algorithm for nonlinear optimization .

用量子行为的微粒群算法优化SVM子问题，解决二次规划的优化问题。

Then optimize sub problems of support vector machines with Quantum-behaved Particle Swarms Optimization , solve quadratic programming problem .

序列二次规划中Bκ的正定性研究

The Research on Positive Definite Property of B_ κ in Sequential Quadratic Programming

研究了基于遗传算法和逐步二次规划法的混合频域H∞建模方法。

Presents the hybrid H ∞ modeling method in frequency combining the genetic algorithm and the sequential quadratic programming .

在空间分割的基础上，提出了采用四个独立的二次规划神经网络NeuralNetworks（NN）实现方向估计的方法。

In this paper four neural networks for solving quadratic optimization problems are used for direction finding based on spatial partition .

本文结合功率匹配泵，利用序列二次规划法对其数字PID控制器进行了非线性控制寻优，取得了很好的效果。

With this ibea , we have optimized the digital PID controller of aload sensing pump by using sequential quadratic programming method .

OpenGL实用编程技巧两则自动机与程序设计整凸二次规划

Two practical skills for OpenGL programming

二次规划（QP）为NP完全问题。

Quadratic programming ( QP ) is an NP complete problem .

利用MATLAB软件可以求解线性规划、无约束规划、二次规划和有约束非线性规划等优化设计问题。

MATLAB software can solve many kinds of problems in optimal design , such as linear programming , unconstraint programming , quadratic programming and nonlinear constraint programming etc. .

该方法通过构造适当的约束条件，将光纤喇曼放大器的增益和噪声优化问题转变为一有约束非线性规划问题，以序列二次规划（SQP）法作为优化算法进行求解。

This method deals with the optimization problem as a constrained nonlinear programming problem .

此外，SVM等价于解线性凸二次规划问题，这样SVM的解总能获取全局唯一最优值。

In addition , SVM will be equivalent to solving a linear constrained quadratic programming problem so that the solution of SVM is always unique and globally optimal .

基于参数变分原理和二次规划法进行了Voronoi单元的二维弹塑性分析。

The parametric variational principle and quadratic programming method were developed for elastic-plastic Voronoi finite element analysis of two-dimensional problems .

严格凸二次规划的Cholesky预处理

The Preconditioning of Strict Convex Quadratic Programming

解二次规划的一种Karmarkar变型算法

A Variant of Karmarkar 's Algorithm to Solve Quadratic Programming Problems

整个推力分配算法用C语言编程实现。最后，本文对该推力分配优化算法进行仿真，仿真证明了序列二次规划算法在推力分配应用上的成功。

The thrust optimum allocation algorithm is implemented by using the C programming language . Lastly , the simulations about the thrust optimum allocation algorithm are carried out . These simulations indicate that the SQP is applied successfully in thrust allocation .

本文研究求解约束最优化问题的序列二次规划算法（SQP算法）。

In this paper , we are concerned with the sequence quadratic programming ( SQP ) methods for solving constrained optimization problems .

同时还给出了一个针对两种性能指标的最优控制算法：H／V；混合优化控制算法，给出了求解最优控制器的上逼近算法及其凸二次规划求解方法。

An optimal control algorithm : H2 / l1 mixed optimal control which about two index of performance is given . Lower approximation algorithm and its solve of convex quadratic programming are also given in this article . 4 .

贝叶斯方法可用来实现模型中超参数的自适应，同时保持SVR稀疏性和凸二次规划的优点。

Bayesian methods are used to implement model adaptation , while keeping the merits of support vector regression , such as sparseness and convex programming .

本人所在实验室提出了一种基于二次规划的图像缩放算法，在这基础之上，作者使用matlab实现了这个算法，包括图像的显著性提取以及图像的缩放处理。

Own laboratory , put forward a kind of image retargeting algorithm based on quadratic programming , and on this basis , the author uses matlab to realize the algorithm , including significant extraction of image and image zoom processing .

本文在简述序贯二次规划（SQP）方法基本概念的基础上，回顾了该方法的最近进展，我们讨论了诸如下降函数、投影Hesse矩阵校正、信赖域方法等一些很有发展余地的论题。

Recent Progress on sequential quadratic programming ( SQP ) methods is reviewed after a concise introduction of the basic concepts .

针对传统动态优化算法计算效率低的缺点，引入了序列二次规划（SQP）优化算法。

Aiming at disadvantages that the traditional dynamic optimum arithmetic has low computing efficiency , the Sequential Quadratic Programming ( SQP ) was proposed .

本文针对求解不等式约束非线性最优化问题的序列二次规划（SQP）算法进行改进。

In this thesis , we make some modification to some existing sequential quadratic programming ( SQP ) algorithm for solving inequality constrained problems .

由于序列二次规划（SQP）算法具有快速收敛速度，所以它是求解光滑约束优化问题的有效方法之一。

Sequential quadratic programming ( SQP ) method is an efficient method for solving smooth constrained optimization problems because of its fast convergence rate .

然而，传统的SVM的处理需要求解有约束的二次规划问题，这样的处理速度很难满足在线应用，尤其在训练样本数较大的情况下。

However , the conventional SVM needs to resolve the NP-complex quadratic programming problem , the time resuming of which makes it difficult to apply the realtime processing , especially with the large training data set .

第三，采用了NURBS曲线、曲面技术对复杂目标建模，给出了反求NURBS曲线控制点的凸二次规划算法。

Thirdly , the principles of NURBS curve and surface are used to the modeling of complex object , and a protruding quadratic programming algorithm for reconstructing reference points of NURBS curve .

在SQP算法中，保证QP子问题的目标函数的Hessian阵的正定性是非常重要的。若QP子问题的Hessian阵正定，则它是一个严格凸二次规划问题。

In an SQP method , it is important to keep the Hessian of the objective function in the QP problem to be positive definite .

利用灵敏度分析和基于梯度的优化算法即序列二次规划算法（SQP法）求解最优设计参数。

The analytical design sensitivities are combined with a sequential quadratic programming ( SQP ) algorithm to systematically traverse the design space towards the optimal values .

以稳定缠绕条件和壳体强度要求为约束，缠绕层最小质量为优化目标，利用收敛效率较高的序列二次规划算法（SQP）求得了不同爆破压强下的各项最优均衡缠绕参数。

Furthermore , the optimum parameters of winding process can be obtained by using the sequential quadratic programming algorithm and the results are efficient for the convergence .

再将该优化问题转化成单目标优化问题，并对该问题提出了用逐次二次规划的解法（SQP法）。

This non-linear model was further proved , in essence , to be a multi-target optimization problem , and could be transformed into a single-target optimization problem .

选择影响指标的主要工艺参数作为决策变量，以产品理想分子量分布为目标，采用序贯二次规划（SQP）算法对缩聚生产过程进行优化控制。

Selecting main operating parameters as decision variables and desired WMD as control goal , polycondensation production process is controlled by sequential quadratic programming ( SQP ) algorithm .