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Fuzzy logic expert system for evaluating the activity of university teachers

Yıl 2021, Cilt 8, Sayı 4, 991 - 1008, 04.12.2021
https://doi.org/10.21449/ijate.1025690

Öz

Assessing the performance of academics at different levels is increasingly difficult to achieve using traditional methods based mainly on numerical scores in evaluating teaching and research activity. The indexing of academic performance in various international databases with impact indices at different scales has led to the need for advanced computer models, such as expert systems based on fuzzy logic, proposed in this research, which address the evaluation of teachers even in the face of imprecise information and under conditions of uncertainty. In this research, as a contribution and novelty, a fuzzy logic model was developed in which an algorithm was simulated and implemented in Matlab using the Mandami toolkit, which allows inference of the rules of fuzzy logic and visualization. 3D. The system implementation was done by software in Matlab environment, using systems with fuzzy Mandami logic. The result of this pilot study was to test and validate the proposed model through a graphical interface, giving the results according to minimum criteria and with additional explanations.

Kaynakça

  • Ahmed, F., & Toki, M. (2016). A Review on Washing Machine Using Fuzzy Logic Controller. International Journal of Emerging Trends in Engineering, 4(7), 64 67. http://www.warse.org/IJETER/static/pdf/file/ijeter02472016.pdf
  • Bellman, R., & Zadeh, L. (1970). Decision Making in a Fuzzy Environment. Management Sciences, 17(4), 141-164. http://dx.doi.org/10.1287/mnsc.17.4.B141
  • Chennakesava, R. (2008). Fuzzy logic and neural networks. Basic concepts & applications, New Age International Publishers, Darya Ganj, New Delhi-110 002, India.
  • Chuen, L. (1990). Fuzzy Logic in Control Systems: Fuzzy Logic Controller – Part I. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404 418. http://ieeexplore.ieee.org/document/52551
  • Garrido, L. (2012). A Brief History of Fuzzy Logic. Broad research in artificial intelligence and neuroscience, 3(1), 71-77.
  • Łukasiewicz, J., & Tarski, A. (1930). Untersuchungen überden Aussagenkalkül (German). Comptes rendus des séances de la Société des Sciences et des Lettres de Varsovie. CI III, 23, 30–50. English translation: Investigations into the sentential calculus.
  • Mamdani, E., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man Machine Studies, 7(1), 1 13. https://doi.org/10.1016/S0020-7373(75)80002-2
  • McCarthy, J. (1959). Programs with Common Sense at the Wayback Machine (archived October 4, 2013). In Proceedings of the Teddington Conference on the Mechanization of Thought Processes, 756-91. Her Majesty's Stationery Office.
  • Patjoshi R., & Mohapatra, K. (2010). Experimental Investigation on Microcontroller based Elevator Positioning Control System Using Fuzzy-Logic. International Journal of Advanced Technology and Engineering Exploration, 8(5), 88-94.
  • Takagi, T., & Sugeno, M. (1985). Fuzzy Identification of Systems and Its Application to Modeling and Control. IEEE Transactions on Systems, Man, and Cybernetics, SMC-15, 116-132. http://dx.doi.org/10.1109/TSMC.1985.6313399
  • Subbulakshmi, L. (2014). Antilock-braking system using fuzzy logic. Middle-East Journal of Scientific Research, 20(10), 1306 1310, 2014, http://dx.doi.org/10.5829/idosi.mejsr.2014.20.10.232
  • Vijayana, K., Srivastavaa, P.P., Raghunathb, M.K., & Saratchandraa, B. (2011) Enhancement of stress tolerance in mulberry. Scientia Horticulturae, 129(4), 511 519. http://dx.doi.org/10.1016/j.scienta.2011.04.018
  • Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338 353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • Zadeh, L. (1996). Fuzzy logic=computing with words. IEEE Transactions on Fuzzy Systems, 4(2), 103–111. https://doi.org/10.1109/91.493904
  • Zadeh, L. (1968). Fuzzy algorithms. Information and Control, 12(2), 94 102. https://doi.org/10.1016/S0019-9958(68)90211-8
  • Zadeh, L. (1971). Quantitative fuzzy semantics. Information Sciences, 3(2), 159–176. https://doi.org/10.1016/S0020-0255(71)80004-X
  • Zadeh, L. (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3, 28-44. https://doi.org/10.1109/TSMC.1973.5408575

Fuzzy logic expert system for evaluating the activity of university teachers

Yıl 2021, Cilt 8, Sayı 4, 991 - 1008, 04.12.2021
https://doi.org/10.21449/ijate.1025690

Öz

Assessing the performance of academics at different levels is increasingly difficult to achieve using traditional methods based mainly on numerical scores in evaluating teaching and research activity. The indexing of academic performance in various international databases with impact indices at different scales has led to the need for advanced computer models, such as expert systems based on fuzzy logic, proposed in this research, which address the evaluation of teachers even in the face of imprecise information and under conditions of uncertainty. In this research, as a contribution and novelty, a fuzzy logic model was developed in which an algorithm was simulated and implemented in Matlab using the Mandami toolkit, which allows inference of the rules of fuzzy logic and visualization. 3D. The system implementation was done by software in Matlab environment, using systems with fuzzy Mandami logic. The result of this pilot study was to test and validate the proposed model through a graphical interface, giving the results according to minimum criteria and with additional explanations.

Kaynakça

  • Ahmed, F., & Toki, M. (2016). A Review on Washing Machine Using Fuzzy Logic Controller. International Journal of Emerging Trends in Engineering, 4(7), 64 67. http://www.warse.org/IJETER/static/pdf/file/ijeter02472016.pdf
  • Bellman, R., & Zadeh, L. (1970). Decision Making in a Fuzzy Environment. Management Sciences, 17(4), 141-164. http://dx.doi.org/10.1287/mnsc.17.4.B141
  • Chennakesava, R. (2008). Fuzzy logic and neural networks. Basic concepts & applications, New Age International Publishers, Darya Ganj, New Delhi-110 002, India.
  • Chuen, L. (1990). Fuzzy Logic in Control Systems: Fuzzy Logic Controller – Part I. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 404 418. http://ieeexplore.ieee.org/document/52551
  • Garrido, L. (2012). A Brief History of Fuzzy Logic. Broad research in artificial intelligence and neuroscience, 3(1), 71-77.
  • Łukasiewicz, J., & Tarski, A. (1930). Untersuchungen überden Aussagenkalkül (German). Comptes rendus des séances de la Société des Sciences et des Lettres de Varsovie. CI III, 23, 30–50. English translation: Investigations into the sentential calculus.
  • Mamdani, E., & Assilian, S. (1975). An experiment in linguistic synthesis with a fuzzy logic controller. International Journal of Man Machine Studies, 7(1), 1 13. https://doi.org/10.1016/S0020-7373(75)80002-2
  • McCarthy, J. (1959). Programs with Common Sense at the Wayback Machine (archived October 4, 2013). In Proceedings of the Teddington Conference on the Mechanization of Thought Processes, 756-91. Her Majesty's Stationery Office.
  • Patjoshi R., & Mohapatra, K. (2010). Experimental Investigation on Microcontroller based Elevator Positioning Control System Using Fuzzy-Logic. International Journal of Advanced Technology and Engineering Exploration, 8(5), 88-94.
  • Takagi, T., & Sugeno, M. (1985). Fuzzy Identification of Systems and Its Application to Modeling and Control. IEEE Transactions on Systems, Man, and Cybernetics, SMC-15, 116-132. http://dx.doi.org/10.1109/TSMC.1985.6313399
  • Subbulakshmi, L. (2014). Antilock-braking system using fuzzy logic. Middle-East Journal of Scientific Research, 20(10), 1306 1310, 2014, http://dx.doi.org/10.5829/idosi.mejsr.2014.20.10.232
  • Vijayana, K., Srivastavaa, P.P., Raghunathb, M.K., & Saratchandraa, B. (2011) Enhancement of stress tolerance in mulberry. Scientia Horticulturae, 129(4), 511 519. http://dx.doi.org/10.1016/j.scienta.2011.04.018
  • Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338 353. https://doi.org/10.1016/S0019-9958(65)90241-X
  • Zadeh, L. (1996). Fuzzy logic=computing with words. IEEE Transactions on Fuzzy Systems, 4(2), 103–111. https://doi.org/10.1109/91.493904
  • Zadeh, L. (1968). Fuzzy algorithms. Information and Control, 12(2), 94 102. https://doi.org/10.1016/S0019-9958(68)90211-8
  • Zadeh, L. (1971). Quantitative fuzzy semantics. Information Sciences, 3(2), 159–176. https://doi.org/10.1016/S0020-0255(71)80004-X
  • Zadeh, L. (1973). Outline of a New Approach to the Analysis of Complex Systems and Decision Processes. IEEE Transactions on Systems, Man, and Cybernetics, SMC-3, 28-44. https://doi.org/10.1109/TSMC.1973.5408575

Ayrıntılar

Birincil Dil İngilizce
Konular Eğitim, Eğitim Araştırmaları
Yayınlanma Tarihi December
Bölüm Makaleler
Yazarlar

V. Florin POPESCU Bu kişi benim (Sorumlu Yazar)
National Defense University
0000-0002-9972-9904
Romania


M. Sorin PİSTOL Bu kişi benim
European Asylum Support Office
0000-0003-1172-3637
Malta

Yayımlanma Tarihi 4 Aralık 2021
Yayınlandığı Sayı Yıl 2021, Cilt 8, Sayı 4

Kaynak Göster

APA Popescu, V. F. & Pistol, M. S. (2021). Fuzzy logic expert system for evaluating the activity of university teachers . International Journal of Assessment Tools in Education , 8 (4) , 991-1008 . DOI: 10.21449/ijate.1025690

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