The purpose of this thesis is to provide a modified HS and a BFGS-type method.
本论文的目的是提出一种修改HS方法和一种BFGS类型方法。
Numerical results and numerical comparison with BFGS, and so on are also given.
数值结果及与BFGS法等其它变尺度法的数值比较。
The paper proposes a nonmonotonic BFGS-trust-region algorithm for unconstrained optimization.
给出了一个解无约束最优化问题的非单调的新的BFGS校正的信赖域算法。
An approximate Gauss Newton based BFGS method for solving symmetric nonlinear equations is presented.
给出一个解非线性对称方程组问题的近似高斯·牛顿基础bfgs方法。
BFGS algorithm is one of the most effective methods in solving the non-constrained optimization problems.
BFGS算法是解无约束优化问题的公认的最有效的算法之一。
An estimated logarithm of parameter with good stability and quick convergence BFGS logarithm is suggested.
提出一种稳定性好、收敛速度快的参数估计算法——BFGS算法。
The one dimension search method of second differential algorithm is used in the Variable metric method of BFGS.
在BFGS变尺度算法中所用的一维搜索方法是二次插值算法。
In this paper, a smooth approximation-BFGS method for solving inequality constrained nonlinear programming is presented.
本文对不等式约束非线性规划提出一种光滑逼近- BFGS法。
In the methods of nonlinear analysis, along with the normal variable stiffness methods, the improved BFGS method is used.
非线性分析的方法，除采用一般的变刚度法之外，还采用了改进的BFGS法。
The efficiency of verifying validity of the numerical algorithm is more superior than the standard limited memory BFGS algorithm.
进行数值实验验证算法的有效性，比标准有限记忆BFGS算法更优越。
The first part of this paper mainly introduces the history of BFGS algorithm and the present situation of modified BFGS algorithm.
本文的前半部分介绍了BFGS算法的历史和修正bfgs算法的研究现状。
By using a modified BFGS formula, a BFGS-type trust region method with line search technique for unconstrained optimization problems is proposed.
利用一个修正的BFGS公式，提出了结合线搜索技术的BFGS -信赖域方法，并在一定条件下证明了该方法的全局收敛性和超线性收敛性。
To improve the efficiency and robustness of constraint solving algorithms, a hybrid algorithm to integrate chaos method into BFGS algorithm was proposed.
为了提高约束求解的效率和鲁棒性，提出了一个将混沌方法嵌入BFGS算法的约束求解混和算法。
In Chapter 1, we recall the foundational knowledge about conjugate gradient method and some famous researches, and describe the BFGS and BFGS-TYPE formulas.
第一章，回顾有关共轭梯度方法的基本知识及一些著名成果，描述了BFGS和BFGS - TYPE公式。
The new identification method for nonlinear systems is presented, which combinesrecursive least-square (RLS) parameter estimation with nonlinear programming (BFGS).
所提出的辨识新方法，以递推最小二乘（RLS）参数估计与非线性规划（BFGS）为主体。
The BFGS algorithm applied in GCS is analyzed and pointed out two shortcomings: (1) always trapped in local optimal solution; (2) can not pass through the critical point.
分析了BFGS算法在约束求解中的应用，指出了在约束求解这一特定的领域利用BFGS算法进行约束求解的两大缺陷：（1）容易陷入局部最优解：（2）无法穿越临界点。
Combining the BFGS method with the chaos optimization method, a hybrid approach is proposed to solve nonlinear optimization problems with boundary restraints of variables.
把BFGS方法与混沌优化方法相结合，基于混沌变量提出一种求解具有变量边界约束非线性最优化问题的混合优化方法。
Because of the density of the matrices produced by the BFGS method generally, it must adopt particular sparse technique for solving large dimensional optimization problems.
由于BFGS算法产生的矩阵一般是稠密的，因此当它用于求解大规模最优化问题时需采用一定的稀疏技巧。
Based on the graphical implication of reliability index, applying chaos algorithm and BFGS algorithm, a new reliability analysis method on the basis of hybrid chaos algorithm was presented.
根据可靠度指标的几何意义，联合应用混沌算法和BFGS算法，提出了基于混沌混合算法的可靠度分析方法。
Based on the graphical implication of reliability index, applying chaos algorithm and BFGS algorithm, a new reliability analysis method on the basis of hybrid chaos algorithm was presented.
根据可靠度指标的几何意义，联合应用混沌算法和BFGS算法，提出了基于混沌混合算法的可靠度分析方法。
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