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Erschienen in: Neural Computing and Applications 1/2017

18.05.2016 | Original Article

Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC’s GDP forecasting

verfasst von: Pei-Han Hsin, Chun-I Chen

Erschienen in: Neural Computing and Applications | Sonderheft 1/2017

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Abstract

The traditional Grey forecasting model, GM(1,1), is characterized by its linear property. The Nash nonlinear Grey Bernoulli model further increases the forecasting accuracy by considering two governing parameters in the model. Because of the multiple Nash solutions, this study uses trembling-hand perfect equilibrium to refine the NNGBM and then obtains higher forecasting accuracy. This study mathematically proves that the proposed model is feasible and efficient. Finally, NNGBM with trembling-hand perfect equilibrium is used to forecast GDP of four fast-growing countries, Brazil, Russia, India and China, which are abbreviated as BRIC. The results show that BRIC’s GDP is keeping on growing.

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Metadaten
Titel
Application of trembling-hand perfect equilibrium to Nash nonlinear Grey Bernoulli model: an example of BRIC’s GDP forecasting
verfasst von
Pei-Han Hsin
Chun-I Chen
Publikationsdatum
18.05.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe Sonderheft 1/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2340-6

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