Hierarchical cluster based evaluation system for computer courses
- 229 Downloads
With continuous deepening of educational reform, educators attach more and more importance to efficient computer lesson. To improve effectiveness of computer course learning evaluation, a kind of computer course learning evaluation system based on game compromise analytic hierarchy process (AHP) is proposed in this paper. Firstly, overall structure of computer course learning evaluation system is constructed based on AHP model, scale and pairwise comparison matrix are given, and quantitative analysis is made to efficient computer lesson teaching evaluation, so as to provide reference for efficient computer lesson teaching evaluation; secondly, subjective weight of computer course learning evaluation index is determined based on analytic hierarchy process (AHP), comprehensive weight of index evaluation is obtained through game compromise method, and computer course learning system decision method based on ordering is constructed; finally, effectiveness of algorithm is verified through example test.
KeywordsGame compromise Analytic hierarchy process Efficient computer lesson Evaluation system
This research is supported by Western First-Class Discipline Education Subject Fundation of Ningxia Normal University(Grant No YLXKYB1704), Natural Science Foundation of Ningxia(Grant No NZ16250), Undergraduate Teaching Project Funded Projects of Ningxia Normal University, The 12th Five-year Plan of Ningxia Key Discipline-Fundamental Mathematics. The author are grateful to the editors and reviews for their valuable suggestions.
- 1.Yang, Z.H., Wang, C., Shi-Jie, H.U.: Study on fuzzy comprehensive evaluation system of city gas pipeline based on AHP. J. Saf. Environ. 13(2), 257–260 (2013)Google Scholar
- 2.Lu, J., Han, Z.: Construction project risk fuzzy comprehensive evaluation based on AHP. In: Second International Conference on Electric Technology and Civil Engineering. IEEE Computer Society, pp. 700–704 (2012)Google Scholar
- 3.Hamza, R., Muhammad, K., Nachiappan, A., González, G.R.: Hash based encryption for keyframes of diagnostic hysteroscopy. IEEE Access (2017). https://doi.org/10.1109/ACCESS.2017.2762405
- 4.Fernandes, S.L., Gurupur, V.P., Sunder, N.R., Arunkumar, N., Kadry, S. A novel nonintrusive decision support approach for heart rate measurement. Pattern Recognit. Lett. (2017). https://doi.org/10.1016/j.patrec.2017.07.002
- 5.Arunkumar, N., Ramkumar, K., Venkatraman, V., Abdulhay, E., Fernandes, S.L., Kadry, S., Segal, S.: Classification of focal and non focal EEG using entropies. Pattern Recognit. Lett. 94, 112–117 (2017)Google Scholar