Important Evaluation Model of University Mathematics Curriculum
DOI:
https://doi.org/10.54097/hset.v49i.8523Keywords:
Data envelope analysis; Entropy weight method; ARIMA module; Neural network.Abstract
Mathematics is the foundation of all subjects, and every great progress of human beings has the strong support of mathematics. Mathematics has shown an extremely important role in university education and the importance of mathematics is increasing. With the differentiation of objective environment, the personalization of individual disciplines, the subjective learning attitude, and the interactive influence between various disciplines, a lot of precise statistical requirements are put forward. In this context, the study of the importance model of university mathematics curriculum is helpful for college students to better study and plan, and also provides a reference for other industries such as education. This paper combines the performance data of mathematics students of each major and each class. It also combines the relevant characteristics of college students themselves, and puts forward suggestions on the connection of middle school and university mathematics and the subsequent study.
Downloads
References
Jiang Qiyuan. mathematical model[M]. Beijing;Higher Education Press,1993.
Kahn J. S., McIntosh K. History and recent advances in discovery. Pediatr Infect Dis J 2005; 24: S223-7.
Hui D. S. C., Zumla A. Severe Acute Respiratory Syndrome, Epidemiologic, and Clinical Features. Infect Dis Clin North Am 2019, 33: 869-889.
de Wit E., van Doremalen N., Falzarano D., et al. SARS and MERS: recent insights into emerging. Nat Rev Microbiol 2016, 14: 523-34.
Willman M., Kobasa D., Kindrachuk J. A Comparative Analysis of Factors Influencing Two Outbreaks of Middle Eastern Respiratory Syndrome (MERS) in Saudi Arabia and South Korea. Viruses, 2019.
Lu H., Stratton C. W., Tang Y. W. Outbreak of Pneumonia of Unknown Etiology in Wuhan China: the Mystery and the Miracle. J. Med. Virol. 2020, 25678.
Imai N., Dorigatti I., Cori A., Donnelly C., Riley S., Ferguson NM. Report 2: Estimating the potential total number of novel Coronavirus cases in Wuhan City, China, 2020.
Akaike H., A new look at the statistical model identification. IEEE Transactions on Automatic Control, 1974, 19(6): 716-723.
Lim H.-I. A Linear Regression Approach to Modeling Software Characteristics for Classifying Similar Software. 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), 2019, 942-943.
Wu J., Liu C., Cui W., and Zhang Y. Personalized Collaborative Filtering Recommendation Algorithm based on Linear Regression. 2019 IEEE International Conference on Power Data Science (ICPDS), 2019, 139-142.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
