Single-step ahead prediction based on the principle of concatenation using grey predictors |
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| Authors: | Erdal Kayacan Okyay Kaynak |
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| Affiliation: | 1. State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou 310007, China;2. Department of Automation, Shanghai Jiaotong University, Shanghai 200240, China;1. Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Schubertstraße 42, D-01309 Dresden, Germany;2. Department of Human Genetics, Medical Faculty, Ruhr-Universität Bochum, Universitätsstraße 150, D-44780 Bochum, Germany;3. Faculty of Health, University Witten/Herdecke, Alfred-Herrhausen-Strasse 50, 58448 Witten, Germany |
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| Abstract: | In literature a number of different methods are proposed to improve the prediction accuracy of grey models. However, most of them are computationally expensive, and this may prohibit their extensive use. This paper describes a much simpler scheme, based on the principle of concatenation, in which unit step predictions are concatenated by replacing the missing outputs by their previously predicted values. Despite its extreme simplicity, it is shown that the predicted values thus derived results in a better performance than the methods proposed in the literature. Simulation studies show the effectiveness of the proposed algorithm when applied to nonlinear function predictions. |
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