Fuzzy evaluation method using fuzzy rule approach in multicriteria analysis
DOI:
https://doi.org/10.2298/YJOR0801095OKeywords:
fuzzy evaluation, multicriteria analysis, approximate reasoning, teaching qualityAbstract
A multicriteria analysis in ranking the quality of teaching using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the quality of teaching in several courses. The proposed method introduces normalizing data which dampen the extreme value that exists in the data. The use of the model is suitable in evaluating situations that involve subjectivity, vagueness and imprecise information. Experimental results are comparable and the method performs better in some domains. .References
Biswas, R., “An application of fuzzy sets in student’s evaluation”, Fuzzy Set and Systems, 74 (1995) 197-194.
Capaldo, G., and Zollo, G., “Applying fuzzy logic to personnel assessment: A case study”, Omega The International Journal, 29(6) (2001) 585-597.
Chen, S.M., and Lee, C.H., “New methods for students’ evaluation using fuzzy sets”, Fuzzy Sets and Systems, 104 (1999) 209-218.
Chu, F., “Fuzzy multicriteria decision-making in distribution of factories- An Application of Approximate Reasoning", Fuzzy Sets and Systems, 71 (1995) 197-205.
Chu, F., “Quantitative evaluation of university teaching quality – An application of fuzzy set and approximate reasoning”, Fuzzy Sets and Systems, 37 (1990) 1-11.
Chou, T.Y., and Liang, G.S., “Application of a fuzzy multi-criteria decision-making model for shipping company performance evaluation”, Maritime Policy & Management, 28(4) (2001) 375-392.
Kuo, Y.P., and Chen, L.S., “Using the fuzzy synthetic decision approach to assess the performance of university teachers in Taiwan”, International Journal of Management, 19(4) (2002) 593-603.
Lee, K.M., Cho, C. H., and Kwang, H.L., “Ranking fuzzy values with satisfaction function”, Fuzzy Sets and Systems, 64 (1994) 295-309.
Liang, G., and Wang, A., “Personnel placement in a fuzzy environment”, Computers Operations Research, 19 (1992) 107-121.
Pedrycz, W., and Gomide, F., An Introduction to Fuzzy Sets Analysis and Design, The MIT Press, England, 1998.
Saaty, T.L., The Analytic Hierarchy Process, RWS Publications, Pittsburgh, 1995.
Sonja, P.L., “Personnel selection fuzzy model”, International Transactions in Operational Research, 8(1) (2001) 89-105.
Trajkovski, G., "A fuzzy framework for expert system evaluation", Proceedings Joint Meeting of the 5th World Multiconference on Systematics, Cybernatics and Informatics, Orlando, Florida, 2001.
Turban, E., Zhou, D., and Ma, J., “A methodology for grades of journals: A fuzzy set-based group decision support system”, Proceedings of the 33rd Hawaii International Conference on System Science, 2000.
Turksen, I.B., and Wilson, I.A., “A fuzzy sets preference model for consumer choice”, Fuzzy Sets and Systems, 68 (1994) 253-266.
Weon, S., and Kim, J., “Learning achievement evaluation strategy using fuzzy membership function”, ASEE/IEEE Frontiers in Education Conference, 2001, 19-24.
Downloads
Published
Issue
Section
License
Copyright (c) 2008 YUJOR
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.