The pure prediction problem of a stationary random sequence passing through a linear time-invariant system is discussed. 本文讨论了平稳随机序列通过线性时不变系统后的纯预测问题。
The parameters ε/ k, d and m s for pure fluids were regressed from the experimental data of the vapor-liquid phase equilibria, and such parameters could lead to good prediction for surface tension. 从纯流体汽液相平衡数据回归得分子的链节作用参数ε/k、d和ms,这些参数预测纯流体表面张力时可获得较好结果。
The results show that the method can efficiently improve the prediction of the saturated liquid volume of pure substances in the near critical region when combined with PR equation of state, however it is uncertain to improve the prediction of the saturated liquid volume of mixtures. 结果表明:该方法结合PR方程能有效地改进纯组分近临界液相体积的预测,但不一定能改进混合物液相体积预测;
At the same time the sufficient and necessary conditions which there exist regularity feedback control such that the closed loop system is a pure prediction system was given. 并给出了存在正则反馈控制使得闭环系统为纯预报离散广义系统的充要条件。
The comparison between the PEAP with the prediction mechanism and the pure EAP without prediction proves that the prediction mechanism presented in this paper played a key role in improve the routing performance. 并通过对比在相同场景下拥有预测机制的PEAP协议与没有预测的EAP协议的网络性能,证明了本文所提预测机制对网络性能的提升起了明显作用。