Most procedural programming languages have some kind of control statements, and there is often overlap among languages. 大多数程序化的编程语言都提供了某种形式的控制语句,这在语言间通常是共通的。
The proposed approach is robust to local minima of the energy functional because it is minimized by dynamic programming method in the whole energy space. 由于采用了动态规划法并在整个能量空间中搜索能量泛函的极值,算法对能量泛函的局部极值有较强的鲁棒性。
With the restriction of water demand and supply, the objective function optimal value was calculated by sequential quadratic programming. 以需水量和可供水量为约束条件,采用序列二次规划法求解函数最优值。
We start by covering deterministic and stochastic dynamic optimization using dynamic programming analysis. 我们会以使用动态规划分析来处理确定及随机的动态最适化作为开始。
Then, the suboptimal control law is achieved using the dynamic programming principle. 然后,使用动态规划得到增广系统的次优控制律。