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

by Lovi Raj Gupta, Avneet Kaur Dhawan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 37 - Number 6
Year of Publication: 2012
Authors: Lovi Raj Gupta, Avneet Kaur Dhawan
10.5120/4613-6607

Lovi Raj Gupta, Avneet Kaur Dhawan . Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors. International Journal of Computer Applications. 37, 6 ( January 2012), 25-29. DOI=10.5120/4613-6607

@article{ 10.5120/4613-6607,
author = { Lovi Raj Gupta, Avneet Kaur Dhawan },
title = { Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 37 },
number = { 6 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume37/number6/4613-6607/ },
doi = { 10.5120/4613-6607 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:12.447037+05:30
%A Lovi Raj Gupta
%A Avneet Kaur Dhawan
%T Diagnosis, Modeling and Prognosis of Learning System using Fuzzy Logic and Intelligent Decision Vectors
%J International Journal of Computer Applications
%@ 0975-8887
%V 37
%N 6
%P 25-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
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.

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Index Terms

Computer Science
Information Sciences

Keywords

Learning System Parametric Prognosis Modeling Intelligent Decision vectors Higher Education

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