基于随机有限元的梯度优化算法引入拥有随机参数的框架可靠度分析。
The gradient optimization algorithm based on the stochastic finite element was adopted to analyze the reliability of the frame with stochastic parameters.
神经网络的训练采用一阶梯度优化算法，利用点堆中子动力学模型产生训练样本。
The first order gradient optimization algorithm is employed to train the network. The training samples stem from the neutron kinetics of the point-reactor.
讨论带不等式和等式约束优化问题，提出了求解非线性规划问题的广义摄动梯度投影算法。
In this paper, the constrained optimization problem is discussed to arrive at a general perturbed gradient projection method for solution.
传统的模糊c -均值(FCM)聚类是一种基于梯度下降的优化算法，该方法对初始化较敏感，且易陷入局部极小。
The traditional fuzzy C-means (FCM) algorithm is an optimization algorithm based on gradient descending. it is sensitive to the initial condition and liable to be trapped in a local minimum.
共轭梯度法是最优化中最常用的方法之一，它具有算法简便、不需要矩阵存储等优点，十分适合于大规模优化问题。
Conjugate gradient method, which can be easily computed and requires no matrix storage, is one of the most popular and useful method for solving large scale optimization problems.
实验结果表明共扼梯度最优化迭代算法是鲁棒的、快速收敛的，并且大量节省内存。
Experiment results show that the conjugate gradient reconstruction algorithm is robust, rapid convergent, and memory saved.
PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。
Pr conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems, however, its global convergence has not been solved for a long time.
就随机并行梯度下降(SPGD)最优化算法在光束净化系统中的应用展开研究。
This paper researches the application of the stochastic parallel gradient descent (SPGD) optimization algorithm on the beam cleanup system.
然后利用这种模式的特点，在线优化算法相结合的策略梯度估计及随机逼近而得。
Then by utilizing the features of this model an online optimization algorithm that combines policy gradient estimation and stochastic approximation is derived.
随机并行梯度下降(SPGD)算法可以对系统性能指标直接优化来校正畸变波前。
The stochastic parallel gradient descent (SPGD) algorithm can optimize the system performance indexes directly to correct wavefront aberration.
在分析电容层析成像基本原理和图像重建算法的基础上，提出一种结合正则化优化修正的共轭梯度算法。
Based on the analysis of basic principle of electrical capacitance tomography and the image reconstruction algorithm, a conjugate gradient algorithm with optimized regularization is proposed.
为确定多层人工神经网络的权值和阈值建立了混合求解方法，即迭代前期采用BP算法而迭代后期采用梯度优化法进行计算。
Mixed method is built to calculate the weights and thresholds of multi-layer neural network by utilize BP algorithm and terraced optimizations.
为确定多层人工神经网络的权值和阈值建立了混合求解方法，即迭代前期采用BP算法，而迭代后期采用梯度优化法进行计算。
Mixed method was built to calculate the weights and thresholds of multi-layer neural network by utilize BP algorithm and terraced optimizations.
利用优化问题的非线性共轭梯度法与混沌优化方法相结合，提出了一种新的混合优化算法。
A new hybrid algorithm which combines the chaos optimization method and the nonlinear conjugate gradient method approach having an effective convergence property is proposed.
本文使用信赖域策略结合投影梯度算法来解约束优化问题，并给出算法及其收敛性。
This paper is to study the convergence properties of the gradient projection method with trust region strategy for constrained optimization.
提出一种混沌梯度组合全局优化算法，并对该算法进行了收敛性分析。
A coupled optimization algorithm combined gradient search with chaotic search is proposed and its (convergence) is discussed.
为了轨道优化的实时计算，构造了一类梯度投影下降算法，并且给出实际应用的具体步骤。
The gradient projection algorithms are constructed for the real-time computation of trajectory optimization, and the concrete steps of the algorithms are also given.
该方法基于MAP算法，通过利用梯度投影的方法对重建结果不断进行迭代优化得到最终的理想高分辨率影像。
In order to attain a high-resolution image, the algorithm is based on the MAP algorithm, solving the optimization by proposed iteration steps with using the gradient projection method.
仿真结果表明，耦合算法能够充分利用梯度搜索的快速性和混沌搜索全局优化的能力。
The simulation results show that the coupled algorithm is able to make full use of the quickness of gradient search and the ability of global optimization of chaotic search.
本文针对传统BP算法存在的两个常见问题进行了讨论，提出了基于步长优化和共轭梯度法的改进BP算法。
This paper discussed two basic problems of conventional BP algorithm. A improved BP algorithm based on step optimum and conjugate gradient was put forword in this paper.
共轭梯度法是求解最优化问题的一类有效算法。
Conjugate gradient methods are important iterative methods for solving optimization problems.
采用人工神经网或梯度爬山算法均存在对优化函数形式有限制及陷入局部最优等局限性。
The approaches based on ANN or gradient hill climb algorithm have limitations such as the function form and local optimum.
将最速下降法与共轭梯度法有机结合起来，构造出一种混合优化算法，并证明其全局收敛性。
Based on the steepest descent method and the conjugate gradient method, a hybrid algorithm is proposed in this paper, and its global convergence is proved.
通过对OFDM的子信道比特分配空间进行分析，本文提出着眼于误比特概率梯度的动态lms算法和全局优化算法。
In this paper, dynamical LMS algorithm and global optimization algorithm, with a view to gradient of error probability, are proposed based on analysis of sub-carries allocation space for OFDM system.
非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分。
Nonlinear programming techniques, branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.
非线性优化技术、分枝定界算法和不完全乔莱斯基分解的预优共轭梯度法是该工作的三个主体部分。
Nonlinear programming techniques, branch and bound algorithms and incomplete Cholesky decomposition conjugate gradient method (ICCG) are the three main parts of our work.
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