Sequential Unconstrained Minimization Techniques (SUMT) are most common and comparatively successful method in constrained optimization.
罚函数法(SUMT)是处理约束优化问题时最常用、也是较为成功的一种方法。
The idea of conjugate gradient path in unconstrained optimization irradiates us to use this method for solving the linear equality optimization subject to bounds on variables.
无约束优化问题的共轭梯度路径构造的思想启迪我们用其来解带线性等式约束和有界变量约束的优化问题。
Unconstrained optimization method is used to find out the effect of input information on water-make.
用无约束最优化方法求解各输入信息对涌水量的影响。
The conjugate gradient method is one of the most efficient methods for solving unconstrained optimization problems.
共轭梯度法是求解无约束优化问题的一类有效方法。
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.
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。
Trust region method is a kind of efficient methods to solve the general unconstrained optimization and its special situation, the nonlinear least squares problems.
对于一般的无约束最优化问题及其特殊情况非线性最小二乘问题而言，信赖域方法是一种有效的方法。
The filled function method is an approach for solving unconstrained global minimization problem.
填充函数法是一种解无约束全局极小化问题的方法。
The paper presents a nonlinear conjugate gradient method for unconstrained optimization problem, and proves its global convergence under exact line searches.
该文提出一种无约束优化非线性共轭梯度法，证明了精确线性搜索下的全局收敛性。
Trust region method is a kind of efficient and robust method to solve general unconstrained optimization.
对于一般的无约束优化问题，信赖域方法是一种比较有效的方法。
At the second part, nonmonotonic trust region method for unconstrained optimization is studied.
第二部分主要研究无约束最优化问题非单调信赖域法。
Penalty function method transfer constrained condition into unconstrained condition.
采用惩罚函数法将约束优化转化为无约束优化。
In this paper, a computer program for determining near earthquake time and space parameters is designed, on the basis of memory gradient method for unconstrained optimization.
基于无约束最优化问题的记忆梯度法，本文设计了测定近震时空参数的计算机程序。
An improved simplex method (ISM) based on Nelder and Meads simplex method (N-M SM) is presented for unconstrained function optimization.
针对无约束函数最优化问题，提出了一种能有效加快收敛速度的改进单纯形算法。
Punishment function is used to transfer the constrained optimization to unconstrained optimization and the Nelder and Mead Method is used to solve this optimization problem.
采用罚函数将约束优化转化为无约束优化，并用单纯形方法求解。
This paper presents a non-monotone curve search method for unconstrained optimization problems and proves its convergence under some mild conditions.
本文提出一类求解无约束优化问题的非单调曲线搜索方法，在较弱条件下证明了其收敛性。
Neural network method for solving global unconstrained minimized problems was investigated and a new neural network model was then proposed.
这里考察了求解无约束总体极小化问题的神经网络方法，提出了一种新的网络求解模型。
The experimental results show that the method has strong adaptability to unconstrained illumination conditions and irregular background, and is efficient in locating license plate.
实验结果表明，该方法在各种光照和复杂背景条件下均有很好的适应性，对牌照定位有很高的准确性。
Conjugate gradient method is an efficient method in solving problems with unconstrained optimization, which is especially efficient in dealing large dimension.
共轭梯度法是求解大规模无约束优化问题的一种有效方法。
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。
A fuzzy sub-stroke extraction method is proposed to resolve the unsteadiness because of the unconstrained written fashion.
论文提出一种模糊子笔画抽取方法，解决了因无限制手写体笔画随意性而使得抽取的子笔画不稳定的问题。
An adaptive filter trust region method for large scale unconstrained optimization is proposed.
提出一种解大规模无约束优化问题的自适应过滤信赖域法。
The experiments indicate that the virtual scene based on this method eliminates the holes phenomena and can realize the unconstrained smooth virtual scene touring.
实验表明，基于本方法建立的通道型虚拟场景消除了漫游过程中的空洞现象，实现了虚拟场景无限制、平滑的漫游。
The experiments indicate that the virtual scene based on this method eliminates the holes phenomena and can realize the unconstrained smooth virtual scene touring.
实验表明，基于本方法建立的通道型虚拟场景消除了漫游过程中的空洞现象，实现了虚拟场景无限制、平滑的漫游。
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