[1]曾庆山,张晓楠.基于EMD和组合模型的太阳黑子时间序列预测[J].郑州大学学报(工学版),2014,35(03):78-82.[doi:10 3969/jissn.1671 -6833.2014.03.019]
　ZENG Qingshan,ZHANG Xiaonan.Sunspots Time-series Prediction Based on EMD and Combination Model[J].Journal of Zhengzhou University (Engineering Science),2014,35(03):78-82.[doi:10 3969/jissn.1671 -6833.2014.03.019]
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基于EMD和组合模型的太阳黑子时间序列预测()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
35
期数:
2014年03期
页码:
78-82
栏目:
出版日期:
2014-06-30

文章信息/Info

Title:
Sunspots Time-series Prediction Based on EMD and Combination Model
作者:
曾庆山; 张晓楠
Author(s):
ZENG Qingshan; ZHANG Xiaonan
School of Eleetrical Engineering, Zhengzhou University, Zhengzhou 450001 , China
Keywords:
sunspot;  combination model;  EMD decomposition ;  forecasting
分类号:
TP391
DOI:
10 3969/jissn.1671 -6833.2014.03.019
文献标志码:
A
Abstract:
Sunspots are non-linear, non-stationary, multi-seale changes time-series, and the observations wereofen interfered by noise. Aeeorling to the eomplexity of sunspots time-series prediction , first of all, this paperpreprocessed the original data through wavelet de-noising method, then the denoised signal was deeomposedinto several lMF components and remainder by EMD. In view of the charaeteristies of the low frequeney andhigh frequeney components, RBF neural network model and SVM model were used to prediet them respeetive.ly, the final predicted value would be got by adding each component’s result at last. The simulation resultsshow that this model has higher prediclion accuracy.
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