1) Lagrange multiplier method
拉格朗日乘子法
1.
With the Lagrange multiplier method, the minimum distance of the center of a circle and a quadric surface was provided and the tangency condition of curve and surface was given.
利用拉格朗日乘子法求解二次曲线和二次曲面之间的最小距离,给出了曲线与曲面相切的条件。
2.
The discrete equation set of the proposed method is due developed by means of the modified weak form functional in which the Lagrange Multiplier Method and jump function approach are used, respectively, to enforce the essential boundary conditions and.
详细论述了移动最小二乘近似的基本原理和具体实施过程 ;采用拉格朗日乘子法处理第一类边界条件 ,应用跳跃函数法解决不同媒质交界面处解函数导数不连续等问题 ,从而基于修正的弱形式泛函的建立 ,导出了算法的离散数学模型。
2) Lagrange multiplier
拉格朗日乘子法
1.
In this paper,adopting the radar cross section as the constraint condition,a new conical aerodynamic configuration is presented using the Lagrange multiplier method,and the minimization problems are solved by the dynamic evolution method.
采用拉格朗日乘子法优化设计了雷达散射截面约束条件下的锥形融合气动外形。
2.
With Lagrange multiplier,Dirichlet boundary conditions are imposed along the essential boundaries.
在有限元三维20结点单元构成的空间网格上构建流形覆盖和权函数,采用拉格朗日乘子法施加位移约束条件,推导了分析静态问题的计算列式。
3.
With the loan s yield as the earning of financial asset and the volatility of loan as a criteria to reflect the risk of loan, a decision making model of loan risk portfolio s optimization was established through the solution of the problem of quadric program using the Lagrange multiplier with minimum risk in the feasible range.
以贷款的收益率为金融资产的收益 ,以贷款收益率的波动为标准反映贷款风险 ,以拉格朗日乘子法为工具求解二次规划 ,建立了在既定组合收益范围内 ,组合风险最小的贷款组合优化决策模型 。
3) Lagrangian multiplier method
拉格朗日乘子法
1.
The dynamic equations were derived applying the Lagrangian multiplier method.
给出了平面——球系统中描述球体姿态的三个欧拉角的具体定义,在此基础上确定了完全描述球形机器人系统的七个状态变量,指出机器人在运动中所受的三个非完整约束,应用拉格朗日乘子法推导出球形机器人动力学方程。
5) Lagrangian method
拉格朗日乘子法
1.
Optimization of integral flange by Lagrangian method.;
整体法兰拉格朗日乘子法优化设计
2.
In the new method,the Lagrangian method with inequality restriction is used to assign the load between the monoblock so as to increase the feasibility a.
在不等式约束条件下,采用拉格朗日乘子法对火电机组负荷最优分配问题进行研究,以提高在实际运行过程中负荷最优分配结果的可行性和实用性。
6) method of lagrange multipliers
拉格朗日乘子法
1.
Moreover,a weight optimization scheme for the multi-kernel was proposed by maximizing the Margin Maximization Criterion(MMC)based on the method of Lagrange multipliers.
进而,使用拉格朗日乘子法优化最大边缘准则(MMC),提出了多重核权值优化算法。
补充资料:拉格朗日插值法
拉格朗日插值法。当掌握的资料多于两项时,根据已知多项对应资料,可用拉格朗日插值法估计某项对应的未知数值。这种方法是线性插值多项式的推广。
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
参考词条