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global convergence相关的网络例句

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

The Lyapunov stability of the proposed robust decentralized controller is analyzed, and the global uniform ultimate boundedness stability with exponential convergence is proved.

对所设计的关节分散鲁棒控制器的 Lyapunov 稳定性进行了分析,证明系统是指数收敛全局一致最终有界稳定的。

The long-term seepage control effects of the surrounding rocks of the underground powerhouse are performed by a stationary seepage analysis method combining the variational inequality formulation of Signorini's type with an adaptive penalty Heaviside function to guarantee the numerical stability and convergence. Meanwhile, the difficulty in finite element mesh generation is reduced and the calculation time and modeling accuracy are balanced with a global model of equivalent modeling and a submodel of accurate modeling for drainage hole array.

为确保数值计算的稳定性和收敛性,采用Signorini型变分不等式和自适应罚函数相结合的稳定渗流分析方法,对厂房围岩的长期渗控效应进行计算分析;同时,采用基于等效模拟的整体模型分析和基于精细模拟的子模型分析相结合的方法,以减小有限元建模难度并协调计算量和计算精度之间的矛盾。

According to the characteristics of strong global search, but weak local search and slow convergence of genetic algorithm, this paper proposed a new hybrid algorithm which combined GA and PSO, and applied it successfully to automatic software test data generation.

针对遗传算法具有较强的全局搜索能力,但局部搜索能力较弱,且收敛速度慢的特点。将遗传算法与粒子群算法结合起来形成新的混合算法,并成功应用到软件测试数据自动生成过程中。

By estimates of the spectral gap, Sobolev inequality and the weak convergence theory of stochastic process, we obtain that the annealing process converges in probability to a neighbourhood of the global minimal set of the potential function.

利用谱隙估计和Sobolev不等式方法以及随机过程的弱收敛理论我们得到这种退火过程依概率收敛到势函数的全局最小点附近。

There are some disadvantages in BP algorithm, such as low rate of convergence, easily falling into local minimum point and weak global search capability. In order to settle these problems, a genetic algorithm was used to train BP neural network to replace classical learning algorithms. An evolutionary neural network learning algorithm was founded.

针对BP算法存在收敛速度慢、容易陷入局部极小值及全局搜索能力弱等缺陷,采用遗传算法训练BP神经网络,取代了一些传统的学习算法,设计了基于进化神经网络的学习算法。

Focusing on some disadvantages in standard BP algorithm, such as low convergence rate, easily falling into local minimum point and weak global search capability, Genetic algorithm is used to optimal the connection weight of BP Algorithm in this paper, and construct a GA-BP algorithm of evolutionary neural network, and the algorithm is applied to the control of BLDCM speed adjusting system.

针对标准BP算法存在全局搜索能力弱和易陷入局部极小点等缺点,本文将遗传算法与BP神经网络相结合,构造了一种新的进化神经网络GA-BP算法,并将该算法应用于无刷直流电机调速系统的控制,仿真结果表明,与传统的PI控制系统相比,该算法得出的电机控制曲线几乎无超调,与基于BP算法的速度控制系统相比较,具有收敛速度快、不易陷入局部极小的优点。

Focusing on the disadvantages in the BP neural network such as low convergence rate,easily falling into local minimum point and weak global search capability,a new method that used GA to train BP neural networks to gain best weights was presented.

针对传统的BP算法存在收敛速度比较慢、容易陷入局部极小值以及全局搜索能力弱等缺陷,提出了神经网络与遗传算法。结合的方法,采用遗传算法。练BP神经网络,优化网络权值。

A Multi-Species Cooperative PSO algorithm is developed using the ideas of species dividing in the bionomical world. The algorithm is shown to have guaranteed convergence to the global optimum. Furthermore, the training strategies of RBF network structures and weights based on the MCPSO aigorithm is proposed. Simulation results show that the algorithm is effective in such fields as chaotic time-sequence forecasting, system identification, speech signal processing and etc.

在分析基本微粒群算法和协同微粒群算法特点的基础上,借鉴生态学中的种群划分思想,设计出一种多种群协同进化微粒群算法,并分析了该算法的收敛性能;在分析径向基函数神经网络结构的基础上,提出了基于多种群协同进化微粒群算法的径向基函数神经网络结构和权值优化设计策略,并在混沌序列预测、系统辨识、语音信号处理等应用仿真实验中验证了算法的有效性。

This paper studies the exponential stability of cellular neural networks with time- varying delay by making use of the homoeomorphism theory, the idea of vector Lyapunov function, M- matrix theory and inequality - technique, offering the grounds for uniqueness of equilibrium point existence and the global exponential stability and estimating the exponential convergence rate index.

利用同胚映射理论、向量Lyapunov函数思想、M-矩阵理论和不等式技术,研究了具有变时滞的细胞神经网络模型的全局指数稳定性,给出了判定平衡点的存在唯一性以及全局指数稳定性的一个判据,并且估计了收敛速度指标。

So, this paper mainly focuses on the search capacity of intelligent algorithms, to improve their convergence speed and solution quality, and avoid them trapping in local optima. We study methods to enhance the global serach ability of an algorithm from the algorithm searching mechanism and spatial structure, and at the same time consider its lobal search ability.

因此,本论文主要围绕智能优化算法的空间搜索能力,从算法搜索机制和搜索空间结构两个方面,研究增强算法的全局搜索能力的方法,同时兼顾局部寻优能力,以避免算法陷入局部最优,提高搜索性能。

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