We show how an optimal sampling plan can be calculated for a limited budget...
我们说明了在有限的预算时，计算如何优化采样计划。
The paper analyze elemental sampling program, and study an optimal sampling policy for environmental monitoring.
本文分析了基本抽样程序，并用来解决环境监测的抽样优化问题。
Basing on these conditions, the method and the algorithm for acquiring optimal sampling frequencies is presented.
基于这些条件，文章给出了优化采样频率的求解方法和算法。
Finally, an algorithm for acquiring optimal sampling frequencies and static optimal scheduling algorithm are presented.
最后，给出了求优化采样频率的算法和控制系统的静态优化调度算法。
The actual computation example shows that the optimal sampling frequency locations are found to be independent of the system response, and solely depend on the nature of the excitation.
实际算例表明，最优采样频率点位置并不依赖于系统的输出，仅仅取决于激励的性质。
Genetic algorithms (GA) together with a boundary sampling strategy are proposed for optimal statistical design.
对于最优统计设计，本文提出了遗传算法(GA)以及边界抽样策略。
Its current control action is obtained by solving, at each sampling instant, a finite horizon open-loop optimal control problem, using the current state of the plant as initial state;
它的当前控制作用是在每一个采样瞬间通过求解一个有限时域开环最优控制问题而获得。
Under simple random sampling scheme without replacement and unknown proportion of population possessing neutral attribute, the optimal allocation of sizes of two sub-samples is given.
对简单随机不放回抽样，在总体非敏感属性个体比例未知的情况下，给出了两个子样本容量的最优配置。
Otherwise, the optimal theoretical sampling number of the larva and the sequential sampling model were obtained.
并确定了该天牛幼虫林间调查的最适理论抽样数和序贯抽样模型。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
A linear quadratic Gaussian (LQG) stochastic optimal control was developed for networked control systems with network-induced delays longer than a sampling period using a time-division control mode.
对于网络诱发延迟大于一个采样周期的网络化控制系统，该文研究了该系统的线性二次Gauss (LQG)随机最优控制问题，提出了一种新的分时控制模式。
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