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Using Taylor Approximation Method to Improve the Predicted Accuracy of GM(1,1), GVM, and GM(2,1)

Tian-Wei Sheu, Phuoc-Hai Nguyen, Phung-Tuyen Nguyen, Duc-Hieu Pham, Ching-Pin Tsai, Masatake Nagai


The purpose of this study is to predict the number of foreign students studying in Taiwan based on the combination of grey model and Taylor approximation method. This combined model can obtain the most optimal predicted values by multi-times approximate calculation to improve the predicted accuracy of GM(1,1), GVM, and GM(2,1). In addition, the researchers used MATLAB software to build a MATLAB toolbox for T-GM(1,1), T-GVM, and T-GM(2,1). The experimental results showed that three prediction models can be adjusted repeatedly until reaches the optimal values and makes the predicted error reduce to the minimum. The results will provide the important information for educational administrators to proactively propose the appropriate policy, and builds the educational development strategy in accordance with the new conditions.


grey model, Taylor approximation method, T-GM(1,1), T-GVM, T-GM(2,1)..

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