[1]YAN Xiu-hong,XU Lun-hui,DONG Shi-chang.Grey neural network and integrated forecasting based on preprocessed data[J].CAAI Transactions on Intelligent Systems,2007,2(4):58-62.
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Grey neural network and integrated forecasting based on preprocessed data

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 4 Page number: 58-62 Column: 学术论文—机器学习 Public date: 2007-08-25
Title:
Grey neural network and integrated forecasting based on preprocessed data
Author(s):
YAN Xiu-hong1; 2; XU Lun-hui2; DONG Shi-chang1
1.Rongshan Middle School of Shunde County,Shunde 528303, China;
2.Institute of Electromechanical Engineering，Jiangxi University of Scie nce and Technology,Ganzhou 341000,China
Keywords:
time series forecasting;  grey neural network; combined forecasting
CLC:
U491.14
DOI:
-
Abstract:
When a system disturbance is too great or a sudden change occurs, the resulting abnormal data can severely disturb the forecasting system. In this sit uation，running a forecasting model before abnormalities in the original data ar e identified produces misleading results. In this paper, an improved grey neural network forecasting model and integrated forecasting method are proposed on the basis of data modification. Several forecasting models were tested based on tim e sequences of passenger volume in Nanchang Railway Station. After comparing mod el predictions with real data, it became clear that prediction accuracy is consi derably improved with revised data, or an improved grey model, or a combined gre y neural network. But the data modification must be done properly. Not all data should be modified, it is only necessary to modify abnormal data in order to mai ntain balance between the data tendency and forecasting sensitivity.
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