Power system load forecasting using stochastic system state model identification technique is proposed.
本文将随机系统状态模型辨识技术用于电力系统负荷预报。
It is not necessary to assume the concrete stochastic process model for a repairable system when we estimate the failure hour by means of the grey forecasting model.
认为运用灰色预测模型来估计可修复系统的故障时刻，不必假定系统的随机过程模型。
Based on the dynamic and stochastic characteristic of short-term traffic volume, an approach combined wavelet analysis and fuzzy Markov forecasting model is put forward.
基于短时交通量时间序列的随机波动特征，提出一种小波分析和模糊马尔柯夫结合的预测方法。
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