# Evaluation and Prediction of Higher Education System Based on AHP-TOPSIS and LSTM Neural Network
## 5 Performance Evaluation
### Experimental Results with Policy Influence  
We apply source data to the improved LSTM network and then obtain experimental results shown in Figure 10. We find that under the influence of policies, the predicted values of each indicator exhibit different degrees of improvement relative to those without policy. Firstly, the proportion of masters and doctors and the proportion of employed persons receiving higher education are remarkably elevated by the policies, showing that our policies can significantly improve the popularization rate of higher education. However, economic indicators, including the proportion of higher education expenditures in GDP and the ratio of research and development (R&D) to GDP, present a small improvement. According to official data from the Ministry of Education of China, the proportion of national fiscal expenditures in education to GDP has remained above 4% for nine years (from 2013 to 2021). It can be seen that the predicted results are more in line with the actual trend. In addition, gross enrollment rate and teacher-student ratio are not apparently affected by the policies, indicating that the existing data for these two indicators have stabilized in our prediction model. However, in fact, gross enrollment rate and teacher-student ratio can reflect the richness of national higher education resources, so it is a significant sign of the development of higher education level. According to the experimental results, our policy adjustment seems to ignore this point, so we need to improve in this aspect. In addition, the indicators of scientific research achievements, including number of published papers and patents, show slight improvements. Existing policies can also be adjusted in this aspect. For example, the government can create and publish research journals on its own. However, note that the prediction results are not reasonable at times. For instance, the predicted international student ratio is apparently too high in comparison with the practical ones. According to the scale of the Chinese population, it is obviously unrealistic for the international student ratio to exceed 0.5. This problem brings up a challenge to the rationality of the prediction model. By examining the data of other research objects, we find that this abnormality is not uncommon. One of the possible explanations may be related to inaccurate data sources. By adopting our evaluation model, we compare China's performance with policy in 2038 with that of several developed countries without policy in 2018, and the results are shown in Figure 11. From the figure, we see that in 2038, China is expected to surpass the levels of higher education in the UK and France and reach the level of Australia in 2018. Certainly there is still a long way to go to catch up with the level of American  
Figure 9: Comparison between China in 2038 and other countries in 2018 (without policies). higher education in 2018. However, in comparison with the situation without policy, the improvement is evident. Impact of Policy Implementation  
In the process of implementing the policies we have designed, students, teachers, universities, communities and country are all impacted. Details are discussed respectively as follows. * For students: There will be gradually increasing opportunities for them to receive higher education, even with allowances for those poorer ones. However, rising gross enrollment rate and innovative requirements from the society lead universities'  
Figure 11: Comparison between China in 2038 and other countries in 2018 (with policy). Figure 10: Comparison of the results with and without policy. students to compete more intensely. Their pressures from learning and competition remain after the policies are implemented, involving better study environments and more abundant teaching resources. * For teachers: During the transformation period (SAME questions what to what), they will be better treated with more benefits and scientific research funds, which promote better research projects.