Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system

This research project introduces a systematic approach for the design of a fuzzy inference system (FIS) based on a class of neural networks to assess the students’ performance. Fuzzy systems have reached a recognized success in several applications to solve diverse class of problems. Currently, the...

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Main Author:	Yeap, Chun Nyen
Format:	Thesis
Language:	English
Published:	2009
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/11536/1/YeapChunNyenMFSKSM2009.pdf
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id	my-utm-ep.11536
record_format	uketd_dc
spelling	my-utm-ep.115362018-06-04T09:53:40Z Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system 2009-10 Yeap, Chun Nyen QA75 Electronic computers. Computer science This research project introduces a systematic approach for the design of a fuzzy inference system (FIS) based on a class of neural networks to assess the students’ performance. Fuzzy systems have reached a recognized success in several applications to solve diverse class of problems. Currently, the combination of fuzzy systems and neural networks is the most successful applications of soft computing techniques with hybrid characteristics and learning capabilities. The developed method uses a fuzzy system augmented by neural networks to enhance some of its characteristics like flexibility, speed, and adaptability, which is called the adaptive neuro-fuzzy inference system (ANFIS). Assessment and reasoning the student performance is not an easy task, especially when it involves many attributes or factors. Moreover, the knowledge of the human experts is acquired to determine the criteria of students’ performance and the decisions about their level of mastery but most of the information is incomplete and vague. To overcome the problem, these projects will carry out the reasoning of the student’s performance based on ANFIS. The method can produce crisp numerical outcomes to predict the student’s performance. The results of the ANFIS approach will be compared to human expert FIS approach. 2009-10 Thesis http://eprints.utm.my/id/eprint/11536/ http://eprints.utm.my/id/eprint/11536/1/YeapChunNyenMFSKSM2009.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Yeap, Chun Nyen Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
description	This research project introduces a systematic approach for the design of a fuzzy inference system (FIS) based on a class of neural networks to assess the students’ performance. Fuzzy systems have reached a recognized success in several applications to solve diverse class of problems. Currently, the combination of fuzzy systems and neural networks is the most successful applications of soft computing techniques with hybrid characteristics and learning capabilities. The developed method uses a fuzzy system augmented by neural networks to enhance some of its characteristics like flexibility, speed, and adaptability, which is called the adaptive neuro-fuzzy inference system (ANFIS). Assessment and reasoning the student performance is not an easy task, especially when it involves many attributes or factors. Moreover, the knowledge of the human experts is acquired to determine the criteria of students’ performance and the decisions about their level of mastery but most of the information is incomplete and vague. To overcome the problem, these projects will carry out the reasoning of the student’s performance based on ANFIS. The method can produce crisp numerical outcomes to predict the student’s performance. The results of the ANFIS approach will be compared to human expert FIS approach.
format	Thesis
qualification_level	Master's degree
author	Yeap, Chun Nyen
author_facet	Yeap, Chun Nyen
author_sort	Yeap, Chun Nyen
title	Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
title_short	Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
title_full	Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
title_fullStr	Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
title_full_unstemmed	Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
title_sort	reasoning of the student’s performance based on adaptive neuro-fuzzy inference system
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems
granting_department	Faculty of Computer Science and Information System
publishDate	2009
url	http://eprints.utm.my/id/eprint/11536/1/YeapChunNyenMFSKSM2009.pdf
_version_	1747814869695987712

Reasoning of the student’s performance based on adaptive neuro-fuzzy inference system

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