Design of virtual simulation practice teaching platform for ideological and political course based on Perceptron model

[1] Hu, S., & Wang, J. (2022). Evaluation algorithm of ideological and political assistant teaching effect in colleges and universities under network information dissemination. Scientific Programming, 2022(2). Search in Google Scholar

[2] Salvati, M., Giacomantonio, M., Pellegrini, V., Cristofaro, V. D., & Leone, L. (2022). Conspiracy beliefs of italian voters for populist parties: the moderated mediational role of political interest and ideological attitudes. Acta psychologica, 223, 103508. Search in Google Scholar

[3] Yuanmeng. (2021). On practice and dilemma of artificial intelligence in collaborative teaching of the ideological and political theory course in colleges and universities. Journal of Intelligent and Fuzzy Systems(5), 1-12. Search in Google Scholar

[4] Honglan, L., & Wu, R. (2021). Study on problems and countermeasures of ideological and political teaching in colleges and universities under the background of new media era. Journal of Intelligent and Fuzzy Systems(1), 1-9. Search in Google Scholar

[5] Hui, J., Zhou, Y., Oubibi, M., Di, W., Zhang, L., & Zhang, S. (2022). Research on art teaching practice supported by virtual reality (vr) technology in the primary schools. Sustainability, 14. Search in Google Scholar

[6] Paszkiewicz, A., Salach, M., Strzaka, D., Budzik, G., Nikodem, A., & Hubert Wójcik, et al. (2021). Vr education support system—a case study of digital circuits design. Energies, 15. Search in Google Scholar

[7] Li, N., Jiang, P., Li, C., & Wang, W. (2022). College teaching innovation from the perspective of sustainable development: the construction and twelve-year practice of the 2p3e4r system. Sustainability, 14. Search in Google Scholar

[8] Feng, C. (2020). An intelligent virtual reality technology in the teaching of art creation and design in colleges and universities1. Journal of Intelligent and Fuzzy Systems, 40(2), 1-12. Search in Google Scholar

[9] Huang, C. Y., Lou, S. J., Cheng, Y. M., & Chung, C. C. (2020). Research on teaching a welding implementation course assisted by sustainable virtual reality technology. Sustainability, 12. Search in Google Scholar

[10] Huo, J., & Yue, X. (2021). Research and implementation of mechanical virtual experiment teaching platform. International Journal of Electrical Engineering Education, 002072092110020. Search in Google Scholar

[11] Luo, Y. (2020). Artificial intelligence model for real-time monitoring of ideological and political teaching system. Journal of Intelligent and Fuzzy Systems, 40(1), 1-10. Search in Google Scholar

[12] Xia, T., & Ahmad, M. T. (2022). Method of ideological and political teaching resources in universities based on school-enterprise cooperation mode. Mathematical Problems in Engineering, 2022. Search in Google Scholar

[13] Hongmei, W., & Songlin, T. (2021). Sentiment analysis of students in ideological and political teaching based on artificial intelligence and data mining. Journal of Intelligent and Fuzzy Systems(3), 1-10. Search in Google Scholar

[14] Lv, J. (2021). Optimization of grouting material mixture ratio based on multi-objective optimization and multi-attribute decision-making. Sustainability, 14. Search in Google Scholar

[15] Wang, M., Zheng, J. H., Li, Z., & Wu, Q. H. (2022). Multi-attribute decision analysis for optimal design of park-level integrated energy systems based on load characteristics. Energy, 254. Search in Google Scholar

[16] Li, Q. (2021). High-resolution pm2.5 estimation based on the distributed perception deep neural network model. Sustainability, 13. Search in Google Scholar

[17] Xuan, H., Zhao, X., You, L., Liu, Z., & Li, Y. (2021). Multiobjective model and improved artificial raindrop algorithm for virtual network mapping. Mobile Information Systems, 2021, 1-10. Search in Google Scholar

[18] Liu, J. (2021). Research on the optimization strategy of innovation and entrepreneurship education teaching mechanism. International Journal of Electrical Engineering Education, 002072092199706. Search in Google Scholar

[19] Zhang, X., Xu, G., & Zhu, J. (2021). Joint latent space models for network data with high-dimensional node variables. Biometrika. Search in Google Scholar

[20] Xiao, Q., Zhang, G., Chen, Z., Hu, H., Wang, S., & Xu, Y. (2022). A novel virtual node selection scheme of cell-based smoothed radial point interpolation method (cs-rpim) for mid-frequency acoustic problems. International Journal of Computational Methods, 19(09). Search in Google Scholar