Conclusion Timeseriesdecomposition 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。
2
This paper proposes an effective timeseries 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。
3
Nonlinear and nonstationary timeseries are decomposed into a series of instrinsic mode functions and a residual trend item by the empirical mode decomposition (EMD).