Author Name:- Anjana Pradeep
Abstract:- The aim of this study is to evaluate the performance of
students using a fuzzy expert system. The fuzzy process is based solely on the
principle of taking non-precise inputs on the factors affecting the
performance of students and subjecting them to fuzzy arithmetic to obtain a
crisp value of the performance. The system classifies each student's
performance by considering various factors using fuzzy logic. Aimed at
improving the performance of fuzzy system, several defuzzification methods
other than the built methods in MATLAB have been devised in this system for
producing more accurate and quantifiable result. This study provides comparison and in depth
examination of various defuzzification techniques like Weighted Average
Formula (WAF), WAF-max method and Quality Method (QM). A new defuzzification
method named as Max-QM which is extended from Quality method that falls within
the general framework is also given and commented upon in this study.
Keywords: Fuzzy logic, Fuzzy Expert System, Defuzzification,
Weighted Average Formula, Quality Method
I. Introduction
An expert system is a software program that can be used to
solve complex reasoning tasks that usually require a (human) expert. In other
words, an expert system should help a novice, or partly experienced, problem
solver, to match acknowledged experts in the particular domain of problem
solving that the system is designed to assist. To be more specific, expert
systems are generally conceptualized as shown in Fig 1. The user makes an
interaction through the interface system and the system questions the user through
the same interface in order to obtain the vital information upon which a
decision is to be made. Behind this interface, there are two other sub-systems
viz. the knowledge base, which is made up of all the domain-specific knowledge
that human experts use when solving that category of problems and the inference
engine, a system that performs the necessary reasoning and uses knowledge from
the knowledge base in order to come to a judgment with respect to the problem
modelled [1].
Expert
system has been playing a major role in many disciplines such as in medicines,
assist physician in diagnosis of diseases, in agriculture for crop management,
insect control, in space technology and
in power systems for fault diagnosis[5]. Some expert systems have been developed
to replace human experts and to aid humans. The use of an expert system is
increasing day by day in today’s world [40]. Expert systems are becoming an
integral part of engineering education and even other courses like accounting
and management are also accepting them as a better way of teaching[4].Another
feature that makes expert system more demanding for students is its ability to
adaptively adjust the training for each particular student on the bases of
individual students learning pace. This feature can be used more effectively in
teaching engineering students. It should be able to monitor student’s progress
and make a decision about the next step in training.
Fig. 1: Expert system
structure
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