文章基本信息

标题：A MULTI-STEP PREDICTION MODEL BASED ON INTERPOLATION AND ADAPTIVE TIME DELAY NEURAL NETWORK FOR TIME SERIES
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作者：LIANG GAO ; YIHUA ZHANG ; MENG ZHANG 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：47
期号：2
页码：870-874
出版社：Journal of Theoretical and Applied
摘要：The drawback of indirect multi-step-ahead prediction is error accumulation. In order to tackle this problem and improve the capacity of adaptive time delay neural network (ATNN) for prediction, a three-stage prediction model SATNN based on spline interpolation and ATNN is presented. With spline interpolation and ATNN, the impact of last prediction errors that would be iterated into the model for the next step prediction is decreased, and then the better prediction can be obtained. The annual sunspot, considered as the benchmark chaotic nonlinear systems, is selected to test the multi-step prediction model. Validation studies indicate that the proposed model is quite effective in multi-step prediction.
关键词：Multi-step Prediction; Time Delay; Adaptive Time Delay Neural Network; Spline Interpolation