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.
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.
通过计算发电机转速和无功补偿节点电压变化量对各控制器参数的轨迹灵敏度，获得目标函数对各控制器参数的梯度，以便于用共轭梯度法寻找最优解。
Trajectory sensitivity approach is used to assess the gradient of the PSS and SVC parameters on the objective function and then conjugate gradient approach is applied to find the optimum solution.
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。
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.
约束最优化方法包括梯度法、共轭方向法、牛顿法和拟牛顿法。
Unconstrained optimization methods include gradient, conjugate direction, Newton, and quasi-Newton methods.
另一方面，采用传统迭代子和共轭梯度法作为光滑子，我们证明了瀑布型多重网格法对一、二维非线性椭圆边值问题，在能量范数下，均可获得最优收敛阶。
Onthe other hand, with traditional iterations and the conjugate gradient(CG) as smoothers, we can show the optimal convergence rate of the cascadic method in energy norm for 1-D and 2-D cases.
另一方面，采用传统迭代子和共轭梯度法作为光滑子，我们证明了瀑布型多重网格法对一、二维非线性椭圆边值问题，在能量范数下，均可获得最优收敛阶。
Onthe other hand, with traditional iterations and the conjugate gradient(CG) as smoothers, we can show the optimal convergence rate of the cascadic method in energy norm for 1-D and 2-D cases.
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