该模型所描述的均衡问题是一个具有均衡约束的均衡问题(EPEC),可用非线性互补方法求解。
This model can be formulated as an equilibrium problem with equilibrium constraints (EPEC) and be solved by a nonlinear complementarity method.
在一致性性质的基础上建立了区间数互补判断矩阵排序的非线性规划模型,算例分析表明该方法是有效可行的。
Based on the consistent propriety, nonlinear programming methods for priorities of interval number complementary judgment matrix which is illustrated by a numerical number are set up.
研究了一类非线性互补约束的均衡问题。
A kind of nonlinear complementarity constraints with equilibrium problems is studied.
在一定的条件下我们证明了非线性互补问题的解是该微分方程系统的平衡点,并且证明了该微分方程系统的稳定性和全局收敛性。
We prove that the solution of a nonlinear complementarity problem is exactly the equilibrium point of differential equation system, and prove the asymptotical stability and global convergence.
提出了基于非线性互补方法的最优潮流算法。
An optimal power flow algorithm based on nonlinear complementarity method is proposed.
针对非线性互补问题,提出了与其等价的非光滑方程的一个下降算法,并在一定条件下证明了该算法的全局收敛性。
This paper presents a new descend algorithm for nonlinear complementarity problems. The global convergence of the algorithm is proved under milder conditions.
利用凝聚函数一致逼近非光滑极大值函数的性质,将非线性互补问题转化为参数化光滑方程组。
By using a smooth aggregate function to approximate the non-smooth max-type function, nonlinear complementarity problem can be treated as a family of parameterized smooth equations.
把解互补问题转化为求非线性映照的不动点。
Firstly, solving complementarity problems is changed into finding a nonlinear mapping's fixed point.
提出了新的弱正则伪光滑非线性互补(ncp)函数,该函数具有良好的性质。
In this paper, we present a new nonlinear complementarity (NCP) function which is piecewise linear-rational, regular pseudo-smooth and has nice properties.
提出了求解非线性互补问题的一个光滑逼近算法,在一定条件下证明了该算法的全局收敛性。
A smoothing approximation algorithm for nonlinear complementarity problems was introduced and the global convergence of the algorithm was proved under milder conditions.
第三章为广义非线性互补问题的自适应信赖域方法。
In chapter 3, we present a self-adaptive trust region method for solving generalized nonlinear complementarity problems.
第二章主要是将求解定义在闭凸多面锥上的广义互补问题(GNCP)转化为一个非线性方程组问题。
In chapter 2, the generalized nonlinear complementarity problem (GNCP) defined on a polyhedral cone is reformulated as a system of nonlinear equations.
仿真结果表明,该方案可以实现模糊控制和神经网络的优势互补,对不确定非线性系统具有很好的控制效果。
Simulation results show that the fuzzy control and neural network can take advantage of each other to possess a good performance in the uncertain nonlinear system.
本文考虑了线性、平方规划和非线性规划问题解的存在唯一、严格互补等性质。
The present paper discusses some properties about existence and unique solution, strict complementarity et al.
针对这一优化问题,通过引入非线性互补问题函数,将原优化问题转化为非线性方程组,并采用半光滑牛顿法进行求解。
By introducing nonlinear complementarity problem function, the original optimization problem is transferred equivalently to a set of nonlinear equations and solved by semi-smooth Newton method.
仿真实验表明,该算法可实现模糊控制和神经网络的优势互补,对非线性复杂系统具有良好的控制性能。
Experiment results show that the algorithm can obtain the advantages of the fuzzy system and the neural network can have better performance in controlling the nonlinear and complex system.
利用双输出口调制器典型的互补输出特性,通过偏置调制器于非线性传输点,可得到一对由NRZ序列边沿触发的明暗脉冲。
The MZM is driven by a non-return-to-zero (NRZ) data sequence and biased at the nonlinear point to generate edge-triggered pulses.
实验结果表明,该算法收敛速度快,稳定性好,是求解非线性互补问题的一种有效算法。
The imitate results manifest that SCO converges fast and stably, and it is an effective algorithm for NCP.
新模型由差分动态系统和非线性互补函数(NCP)转换的半光滑方程系统构成。
The new model is composed of difference dynamic system and semi-smooth equations reformulated by NCP.
新模型由差分动态系统和非线性互补函数(NCP)转换的半光滑方程系统构成。
The new model is composed of difference dynamic system and semi-smooth equations reformulated by NCP.
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