时间序列分解法(Time-series Decomposition)是将时间序列的变化分解成相对稳定的趋势变化、缓慢起伏的不等周期变化、有严格周期的季节变化和没有规律的随机变化四种成分,直...
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Time-series Decomposition 时间序列分解法
Time Series Decomposition Plot 时间序列分解图
time series decomposition for trend 时间序列趋势分解
decomposition of time series [数] [统计] 时间序列分解
Conclusion Time series decomposition is applicable of drug consumption prediction of h...
结论时间序列分解法在医院药品用量预测中有较好的适用性。
This paper proposes an effective time series matching method by combining the empirical mode decomposition (EMD) with the alternative covering algorithm.
将经验模式分解和多层前向网络的交叉覆盖算法相结合,提出一种时间序列相似模式的匹配算法。
Nonlinear and nonstationary time series are decomposed into a series of instrinsic mode functions and a residual trend item by the empirical mode decomposition (EMD).
非线性,非平稳的时间序列经过经验模分解,可以得到一组内模函数和一个基本的趋势项。
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