A Study on a New Way of Thinking Based on Linear Programming to Analyze Civic Education in Colleges and Universities

[1] Tian, Y. (2022). Teaching effect evaluation system of ideological and political teaching based on supervised learning. Journal of Interconnection Networks. Search in Google Scholar

[2] Wang, Z. C. G. (2015). Investigation of the effective combined method of ideological, political education and psychological health education. International Journal of Technology, Management. Search in Google Scholar

[3] 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

[4] Gao, B. (2022). Application of convolutional neural network in emotion recognition of ideological and political teachers in colleges and universities. Scientific Programming. Search in Google Scholar

[5] Zhang, A., & Liu, F. (2017). Research on the computer-based multi-dimensional ideological and political education of college students. Revista de la Facultad de Ingenieria, 32(8), 303-310. Search in Google Scholar

[6] Wang, N. (2021). Ideological and political education recommendation system based on ahp and improved collaborative filtering algorithm. Scientific programming(Pt.13), 2021. Search in Google Scholar

[7] Lei, X. (2015). Discussion on shaping the sound personality of college students in the ideological and political education in colleges and universities. International Journal of Technology, Management(005), 000. Search in Google Scholar

[8] Liang, L. (2016). Research on ideological and political education reform in colleges and universities based on the perspective of faith education. International Journal of Technology, Management. Search in Google Scholar

[9] Li, L. (2023). Effective model of the communication path conversion of ideological and political education in colleges and universities based on new media. Computer-Aided Design and Applications. Search in Google Scholar

[10] Wang, K. (2017). Research on multi-dimensional ideological and political education of college students based on computer platform. Revista de la Facultad de Ingenieria, 32(8), 447-454. Search in Google Scholar

[11] Yihui, P., & Keqin, T. (2011). Method innovation of undergraduate ideological and political education based on network environment. Procedia Engineering, 15(1), 2752-2756. Search in Google Scholar

[12] Lindner, D., Tschiatschek, S., Hofmann, K., & Krause, A. (2022). Interactively learning preference constraints in linear bandits. arXiv e-prints. Search in Google Scholar

[13] Zhang, L., Du, X., Hung, J. L., & Li, H. (2021). Learning preference: development in smart learning environments. Information Discovery and Delivery, ahead-of-print(ahead-of-print). Search in Google Scholar

[14] Kan, Y., Yue, K., Wu, H., Fu, X., & Sun, Z. (2022). Online learning of parameters for modeling user preference based on bayesian network. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems. Search in Google Scholar

[15] Shrestha, S., & Pokharel, M. (2021). Determining learning style preferences of learners. Journal of Computer Science Research, 3(1). Search in Google Scholar

[16] Liu, Y. Z., Fan, Z. P., & Gao, G. X. (2016). An extended linmap method for magdm under linguistic hesitant fuzzy environment. Journal of Intelligent & Fuzzy Systems. Search in Google Scholar

[17] Wang, J. C., & Chen, T. Y. (2020). A novel pythagorean fuzzy linmap-based compromising approach for multiple criteria group decision-making with preference over alternatives. International Journal of Computational Intelligence Systems, 13(1). Search in Google Scholar

[18] Xue, W., Xu, Z., Zhang, X., & Tian, X. (2018). Pythagorean fuzzy linmap method based on the entropy theory for railway project investment decision making. International Journal of Intelligent Systems, 33(1), 93-125. Search in Google Scholar