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penalty function相关的网络例句

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与 penalty function 相关的网络例句 [注:此内容来源于网络,仅供参考]

The reconstructed surface is primarily affected by the quadrilateral meshes and can be improved by introducing penalty function.

其中,影响重构质量的关键因素-四边形网格划分问题,可以通过惩罚项的引入得到改进。

Based on the study of a Pareto optimal for multiobjective optimizations , the Genetic algorithms for MOP is studied. Four new operators are introduced into this MGA that are niche technique, Pareto optimal set, nondominated rank and fuzzy penalty function method.

在研究多目标优化有效解集的基础上,对处理多目标优化的遗传算法进行研究,引入小生境技术、Pareto过滤解集,给出了非劣解排序的方法;对小生境技术引入的优越性进行了比较研究,通过算例检验了本文研究的多目标遗传算法的有效性。

The modified particle swarm optimization is utilized to solve the proposed reactive power optimization model; and combining with non–stationary multi-stage assignment penalty function, the reactive power optimization problem is transferred into a problem to solve extreme-value without constraints, thus the calculation accuracy and global convergence ability of MPSO are effectively improved, and power grid company can achieve maximal economic benefit by means of the proposed algorithm.

应用改进粒子群优化算法求解该无功优化模型,并结合动态调整罚函数法将无功优化问题转化成无约束求极值问题,从而有效地提高了改进粒子群优化算法的全局收敛能力和计算精度,使电网公司取得了最大经济效益。

Stochastic convex programming; Monte Carlo methods; Financial optimization; Convergence with probability one; Optimality condition; Monte Carlo penalty function methods; Nonsmooth optimization; Directional derivative; Subdifferential; Confident interval; Conditional Value-at-Risk; Optimal reinsurance

基础科学,数学,运筹学随机凸规划; Monte Carlo方法;金融优化;以概率1收敛;最优性条件; Monte Carlo罚函数法;非光滑优化;方向导数;次微分;置信区间;条件风险价值;最优再保险

Solving such a system would encounter some intricacies if its leading principal submatrix, i.e. the stiffness matrix, is rank deficient. This is believed to be one of the main reasons that many programmers would unwillingly give up the Lagrange multiplier method but select the penalty function method.

当其中的主子阵亏秩时,求解会遇到许多困难,这些困难往往是导致许多程序员放弃Lagrange乘子法而选择罚函数法的根本原因。

Based on the constrained variation principle, the penalty function suited to electromagnetic field calculation is proposed in this dissertation. Detailed research is conducted on some problems, such as the selection of penalisation parameters, the effect of penalisation parameters to the CPU time and the accuracy of solutions.

本文基于变分原理构造了适合电磁场数值计算的罚函数,得到了系统的控制方程,并对罚因子的选取原则及罚因子对计算精度和计算时间的影响进行了深入研究。

Directed against the problem of stability optimal design on reinforced wainscot of composite materials a kind of mixed optimization algorithm with the combination of mixed penalty function method, Powell method, golden section method, improved coordinates alternation method and genetic algorithm was put forward.

针对复合材料加筋壁板的稳定性优化问题提出了一种用混合罚函数法、Powell法、黄金分割法、改进的坐标轮换法和遗传算法相结合的混合优化算法。

Then the weak formulation of the control equations considering the contact constraint conditions has been developed. Combined the Lagrange multiplier and penalty function methods, the augmented Lagrangian method is used to treat the contact constraint and solved the non-linear and non-smooth problems of the mechanical response perfectly. A finite element model has been applied for the test project of the reinforced slope and to study the mechanism of the interaction of the soil and reinforced material.

本文在Lagrangian网格的控制方程中引入接触界面条件,并采用了经典的Coulomb摩擦模型作为界面切向面力的本构模型,继而发展了考虑接触约束条件的控制方程的弱形式;在求解方法上,综合了Lagrange乘子法与罚方法的优点,采用增广的Lagrangian方法处理接触界面约束,很好地解决了接触问题中的高度非线性和响应不平滑性。

It is no need for this algorithm to linearize the nonlinear system and to decouple the strong-coupling MIMO system. It is also convenient to use the penalty function to solve the restriction.

该算法对非线性系统不需要进行线性化,对带强耦合的MIMO系统不需要解耦,使用罚函数处理约束也非常方便。

This paper proposes an Improved Particle Swarm Optimization algorithm.IPSO adopts a new mutation operator and a new method that congregates some neighboring individuals to form multiple sub-populations in order to lead particles to explore new search space.Additionally,this algorithm incorporates a mechanism with a simple and easy penalty function to handle constraint.Thus,this algorithm has strong global exploratory capability and efficiency while being applied to solve nonlinear constrained optimization problems.

提出了一种改进的粒子群算法(Improved Particle Swarm Optimization,IPSO),使用了一种新型的变异策略,并在搜索过程中将部分邻近的个体聚集成核,从而形成多子群引导粒子探测新的搜索区域,采用了简单易行的罚函数约束处理机制,使算法在求解较难的非线性约束优化问题时具有很强的全局搜索能力与效率。

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