A Forecasting Method Based on Extrema Mean Empirical Mode Decomposition and Wavelet Neural Network

被引：0

作者：

Pan, JianJia ^{[1
]}

Zheng, Xianwei ^{[1
]}

Yang, Lina ^{[1
]}

Wang, Yulong ^{[1
]}

Yuan, Haoliang ^{[1
]}

Tang, Yuan Yan ^{[1
]}

机构：

[1] Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R China

来源：

2015 IEEE 2ND INTERNATIONAL CONFERENCE ON CYBERNETICS (CYBCONF) | 2015年

关键词：

forecasting; empirical mode decomposition; wavelet neural network; IDENTIFICATION;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Time series forecasting is a widely and important research area in signal processing and machine learning. With the development of the artificial intelligence (AI), more and more AI technologies are used in time series forecasting. Multi-layer network structure has been widely used for forecasting problems. In this paper, based on a data-driven and adaptive method, extrema mean empirical mode decomposition, we proposed a decomposition-forecasting-ensemble approach to time series forecasting. Experimental result shows the prediction result by proposed models are better than original signal and EMD based models.

引用

页码：377 / 381

页数：5

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