Call for Paper - November 2022 Edition
IJCA solicits original research papers for the November 2022 Edition. Last date of manuscript submission is October 20, 2022. Read More

Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors

Print
PDF
International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 37 - Number 6
Year of Publication: 2012
Authors:
Lovi Raj Gupta
Avneet Kaur Dhawan
10.5120/4613-6607

Lovi Raj Gupta and Avneet Kaur Dhawan. Article: Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors. International Journal of Computer Applications 37(6):25-29, January 2012. Full text available. BibTeX

@article{key:article,
	author = {Lovi Raj Gupta and Avneet Kaur Dhawan},
	title = {Article: Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {37},
	number = {6},
	pages = {25-29},
	month = {January},
	note = {Full text available}
}

Abstract

In this paper fuzzy Expert Systems are used that are based on fuzzy logic and intelligent decision vectors to handle the quantitative as well as qualitative aspects in measuring the performance of an Educational Institution. The Academic performance of any institution is governed by various parameters that need to be studied in linguistic form. In the present work, a structured mathematical model is developed for individualistic and interdependent effects of these factors. Through fuzzification, we have converted the crisp values into linguistic variables like very good, good, medium, low, high, very high. The two prime functions, each for in-class and out-class activities are formulated then a control function for weaving the parameters within the function is crafted. A regulating function to encompass the dependencies of two prime functions is framed. A decision vector to engross both the prime and control function is originated to suggest the modifications on the present practices for enhancement of academia and overall performance of the institute.

References

  • H. Amin, A. R. Khan, Acquiring Knowledge for Evaluation of Teachers ‘Performance in Higher Education – using a Questionnaire. International Journal of Computer Science and Information Security (IJCSIS) 2(2009), 180-187.
  • Daniel Kahneman, P. S. (1982). Judgment under uncertainty Heuristics and biases . New York: Cambridge University Press.
  • S.Ammar, W.Duncombe, B.Jump, R.Wright, Constructing a fuzzyknowledge-based-system: An application for assessing the financial condition of public schools. Expert Systems with Applications, 27(2004), 349–364.
  • S.M.Bai, S.M.Chen, A new method for students‘ learning achievement using fuzzy membership functions. In Proceedings of the 11th Conference on artificial intelligence, Kaohsiung, Taiwan, Republic of China. (2006).
  • D.Biggs, M.Sagheb-Tehrani, Providing developmental feedback to individuals from different ethnic minority groups using expert systems. Expert Systems, 25(2008), 87-97.
  • A.Berrais, A knowledge-based expert system for earthquake resistant design of reinforced concrete buildings. Expert Systems with Applications, 28 (2005), 519–530.
  • S.M.Chen, C.H.Lee, New methods for students‘ evaluating using fuzzy sets. Fuzzy Sets and Systems, 104(1999), 209–218.
  • D.F.Chang, C.M.Sun, Fuzzy assessment of learning performance of junior high school students. In Proceedings of the 1993 first national Symposium on fuzzy theory and applications, Hsinchu, Taiwan, Republic of China, 1993, pp. 1–10.
  • C. F.Cheung, W.B.Lee, W. M.Wang, K.F.Chu, S.To, A multi-perspective knowledge-based system for customer service management. Expert Systems with Applications, 24(2003), 457–470.
  • T.T.Chiang, C.M.Lin, Application of fuzzy theory to teaching assessment. In Proceedings of the 1994 second national conference on fuzzy theory and applications, Taipei, Taiwan, Republic of China, 1994, pp. 92–97.
  • H. K. H.Chow, K.L.Choy, W.B.Lee, F.T.S.Chan, Design of a knowledge-based logistics strategy system. Expert Systems with Applications, 29(2005), 272–290.
  • J.A.Clark, F.Soliman, A graphical method for assessing knowledge-based systems investments. Logistics Information Management, 12(1999), 63–77.
  • A.J.Day, A.K.Suri, A knowledge-based system for postgraduate engineering courses. Journal of Computer Assisted Learning, 15(1999), 14–27.
  • J. Durkin, Application of Expert Systems in the Sciences. OHIO J. SCI. 90 (1990), 171-179.
  • D.J.Fonseca, G.Uppal, T.J.Greene, A knowledge-based system for conveyor equipment selection. Expert Systems with Applications, 26(2004), 615–623.
  • M.Hamidullah, Comparisons of the Quality of Higher Educations in Public and Private Sector Institutions, PhD Thesis, University of Arid Agriculture Rawalpindi, PAK, 2005.
  • H.Iranmanesh, M.Madadi, An Intelligent System Framework for Generating Activity List of a Project Using WBS Mind map and Semantic Network. Proceedings of World Academy of Science, Engineering and Technology. 30 (2008), 338-345.
  • A.Kazaz, Application of an Expert System on the Fracture Mechanics of Concrete. Artificial Intelligence Review. 19(2003), 177–190.
  • R.Kumra, R.M.Stein, I.Assersohn, Assessing a knowledgebase approach to commercial loan underwriting. Expert Systems with Applications, 30(2006), 507–518.
  • S. H. Liao, Problem solving and knowledge inertia. Expert Systems with Applications, 22(2002), 21–31.
  • J.Ma, D.Zhou, Fuzzy set approach to the assessment of student- centered learning. IEEE Transactions on Education, 43(2000), 237– 241.
  • W.W.Melek, A.Sadeghian, A theoretic framework for intelligent expert systems in medical encounter evaluation. Expert Systems, 26(2009), 87-97.
  • M.Naeemullah, Designing a Model for Staff Development in Higher Education of Pakistan, PhD Thesis, University of Arid Agriculture Rawalpindi, PAK, 2005.
  • T.T.Pham, G.Chen, Some applications of fuzzy logic in rules-based expert systems, Expert System, 19(2002), 208-223.
  • J.Pomar,C.Pomar, A knowledge-based decision support system to improve sow farm productivity. Expert Systems with Applications, 29(2005), 33–40.
  • W. K.Wang, A knowledge-based decision support system for measuring the performance of government real estate investment. Expert Systems with Applications, 29(2005), 901–912.
  • W. K.Wang, H.C.Huang, M.C.Lai, Design of a knowledgebase performance evaluation system: A case of high-tech state-owned enterprises in an emerging economy. Expert Systems with Applications. doi:10.1016/j.eswa.2007.01.032.
  • W.Wen, W. K.Wang, T.H.Wang, A hybrid knowledge based decision support system for enterprise mergers and acquisitions. Expert Systems with Applications, 28(2005a), 569–582.
  • W.Wen, W.K.Wang, C.H.Wang, A knowledge-based intelligent decision support system for national defence budget planning. Expert Systems with Applications, 28(2005b), 55–66.
  • M.H.Wu, Research on applying fuzzy set theory and item response theory to evaluate learning performance. Master Thesis, Department of Information Management, Chaoyang University of Technology, Wufeng, Taichung County, Taiwan, Republic of China,2003.
  • M.R.Shen, Y.Y.Tang, Z.T.Zhang, The intelligent assessment system in Web-based distance learning education. 31st Annual Frontiers in Education Conference, 1(2001), TIF-7-TIF-11.
  • N.H.Yim, S.H.Kim, H.W.Kim, K.Y.Kwahk, Knowledge based decision making on higher level strategic concerns: System dynamics approach. Expert Systems with Applications, 27(2004), 143–158.
  • L.A. Zadeh, Fuzzy sets. Inform. and control, 8 (1965), 338-353.
  • L.A.Zadeh, The concept of a linguistic variable and its application to appropriate reasoning. Information sciences, 8(1975), 43-80.