Forecasting of Taiwans Gross Domestic Product using the Novel Nonlinear Grey Bernoulli Model with ANN Error Correction
- *Corresponding Author:
- Chen CI
Deaprtment of Industrial Management
I-Shou University, Taiwan
Tel: +886 7 6577711
E-mail: [email protected]
Received December 11, 2015; Accepted February 09, 2016; Published February 12, 2016
Citation: Chen CI, Hsin PH (2016) Forecasting of Taiwan’s Gross Domestic Product using the Novel Nonlinear Grey Bernoulli Model with ANN Error Correction.J Glob Econ 4:177. doi:10.4172/2375-4389.1000177
Copyright: © 2016 Chen CI, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Nonlinear Grey Bernoulli Model is proposed to enhance the prediction accuracy. In this study, artificial neural network (ANN) is used to modify the residual error of NGBM. Then, ANN error plus original forecasted value is a new estimated value. The newly proposed method termed NGBM (1,1) with ANN error correction is used to forecast Taiwan’s gross domestic product (GDP). The results show the proposed method is more accurate than NGBM and is proven to be effective in forecasting.