The purpose of this study is to use T-GM(1,1) and T-GM(1,n) to predict the number of teachers and students for admission in Vietnam. T-GM(1,1) and T-GM(1,n) are two prediction models based on Taylor approximation method in grey system theory to improve the predicted accuracy of GM(1,1) and GM(1,n). Two combined models can obtain the most optimal values of prediction by multi-times approximate calculation. In addition, researchers used the MATLAB software to build a MATLAB toolbox for two prediction models. These results of this study not only are conducted to serve as a reference for the educational administrators but also can assist the government in developing future policies regarding educational management. This is critical for improving the overall quality of teaching and learning and improving the quality of education across the country.

The purpose of this study is to use T-GM(1,1) and T-DGM(2,1) to predict the number of foreign students studying in Taiwan. T-GM(1,1) and T-DGM(2,1) are two prediction models based on Taylor approximation method in grey system theory to improve the predicted accuracy of GM(1,1) and DGM(2,1). Two combined models can obtain the most optimal values of prediction by multi-times approximate calculation. In addition, researchers used the MATLAB software to develop a MATLAB toolbox for two prediction models. In this study, results are not only conducted to serve as a reference for the educational administrators but also can assist the government in developing future policies regarding educational management. The accurate prediction of the number of foreign students studying in Taiwan will provide important information for educational managers to continue to attract and efficient use of resources, bring international cooperation for training and scientific research. It will not only help the managers to make good educational scholarship program for foreign students studying in Taiwan but also improve the effectiveness of education for international cooperation in education and training.