Journal ArticleDOI
A new approach for crude oil price analysis based on Empirical Mode Decomposition
Reads0
Chats0
TLDR
The EEMD is shown to be a vital technique for crude oil price analysis and a substantial improvement of EMD which can better separate the scales naturally by adding white noise series to the original time series and then treating the ensemble averages as the true intrinsic modes.About:
This article is published in Energy Economics.The article was published on 2008-05-01. It has received 384 citations till now. The article focuses on the topics: Time series.read more
Citations
More filters
Journal ArticleDOI
Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition
TL;DR: Wang et al. as mentioned in this paper proposed an ensemble empirical mode decomposition (EEMD)-ARIMA model for forecasting annual runoff time series from Biuliuhe reservoir, Dahuofang reservoir and Mopanshan reservoir in China.
Journal ArticleDOI
Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks
Yu Wei,Mu-Chen Chen +1 more
TL;DR: In this article, a hybrid EMD-BPN forecasting approach which combines empirical mode decomposition (EMD) and back-propagation neural networks (BPN) is developed to predict the short-term passenger flow in metro systems.
Journal ArticleDOI
A hybrid model for wind speed prediction using empirical mode decomposition and artificial neural networks
TL;DR: The results show that the proposed EMD–ANN hybrid method is robust in dealing with jumping samplings in non-stationary wind series and the performance of the proposed model is highly satisfactory.
Journal ArticleDOI
Forecasting wind speed using empirical mode decomposition and Elman neural network
TL;DR: A novel EMD-ENN approach, a hybrid of empirical mode decomposition and Elman neural network, is proposed to forecast wind speed, which shows that the proposed approach is suitable for wind speed prediction.
Journal ArticleDOI
Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD
TL;DR: In this article, an adaptive data analysis methodology, ensemble empirical mode decomposition (EEMD), is presented for decomposing annual rainfall series in a rainfall-runoff model based on a support vector machine (SVM).
References
More filters
Journal ArticleDOI
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
TL;DR: In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI
Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Journal ArticleDOI
Ensemble empirical mode decomposition: a noise-assisted data analysis method
Zhaohua Wu,Norden E. Huang +1 more
TL;DR: The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF.
Journal ArticleDOI
A confidence limit for the empirical mode decomposition and Hilbert spectral analysis
Norden E. Huang,Man-Li C. Wu,Steven R. Long,Samuel S. P. Shen,Wendong Qu,Per Gloersen,Kuang L. Fan +6 more
TL;DR: The confidence limit of the method here termed EMD/HSA (for empirical mode decomposition/Hilbert spectral analysis) is introduced by using various adjustable stopping criteria in the sifting processes of the EMD step to generate a sample set of intrinsic mode functions (IMFs) as mentioned in this paper.
Related Papers (5)
Ensemble empirical mode decomposition: a noise-assisted data analysis method
Zhaohua Wu,Norden E. Huang +1 more