Author Name:- Anjana Pradeep, Jeena Thomas
Department of Computer Science & Engineering
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
The few expert systems available in the market present a lot
of opportunities for the students who desire more spotlight and time to learn
the subjects. Some expert systems present an interactive and friendly
environment for students which encourage them to study and adopt a more
practical approach towards learning. The expert systems can also act as an
assistor or substitute for the teacher. Expert systems focus on each student
individually and also keep track of their learning pace. This behavior of an
expert system provides autonomous learning procedure for both student and
teacher, where teachers act as mentor and students can judge their own
performance. Expert system is not only beneficial for the students but also for
the teachers which help them guiding students in a better way.
The
integration of fuzzy logic with an expert system enhances its capability and is
called a fuzzy expert system, as it is useful for solving real world problems
which do not require a precise solution. So, there is a need to develop a fuzzy
expert system as it can handle imprecise data efficiently and reduces the
manual working while enhancing the use of expert system[40].
There
are various factors inside and outside college that results in poor quality of
academic performance of students[2,3]. To determine all the influencing factors
in a single effort is a complex and difficult task. It necessitates a lot of
resources and time for an educator to identify all these factors first and then
plan the classroom activities and approaches of teaching and learning. It also
requires appropriate training, organizational planning and skills to conduct
such studies for determining the contributing factors inside and outside
college. This process of identification of determinants must be given full
attention and priority so that the teachers may be able to develop
instructional strategies for making sure that all the students be provided with
the opportunities to attain at their fullest potential in learning and
performance. By using suitable
statistical package it was found that communication, learning facilities,
proper guidance and family stress were the factors that affect the student
performance. Communication, learning facilities and proper guidance showed a
positive impact on student performance and family stress showed a negative
impact on student performance. It is indicated that communication is more
important factor that affect the student performance than learning facilities
and proper guidance [3].
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