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Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau

The studies of fuzzy relations by Bandler and Kohout, which are also known as the BK products, are well known in the literature as tools to study the composition of relations. In the past, BK products, particularly the BK subproduct, gained remarkable success in developing inference engines for n...

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Main Author: Lim , Chee Kau
Format: Thesis
Published: 2015
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://studentsrepo.um.edu.my/11399/1/Lim_Chee_Kau.pdf
http://studentsrepo.um.edu.my/11399/
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spelling my.um.stud.113992020-07-08T20:01:31Z Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau Lim , Chee Kau QA75 Electronic computers. Computer science The studies of fuzzy relations by Bandler and Kohout, which are also known as the BK products, are well known in the literature as tools to study the composition of relations. In the past, BK products, particularly the BK subproduct, gained remarkable success in developing inference engines for numerous applications. Though successful, there are still some limitations. First of all, this research starts with a survey on a set of inference structures formed by the BK subproduct in previous researches. The survey finds shortcomings in some inference structures. With excluding these candidates, a set of robust inference structures are obtained from the analysis. Secondly, with the understanding that the ordinary type-1 fuzzy sets have limited ability in modeling uncertainty, a more general fuzzy set framework is proposed to improve the performance of BK products. Thus, extending BK products to interval-valued fuzzy sets is another contribution of this thesis. Since the subsethood measure is fundamental to the BK products, two interval-valued fuzzy subsethood measures are also developed in this research. Moreover, this research suggests that, among all the features involved in inferences, certain features should have higher influence compared to the others. Therefore, to distinguish the influence of features towards inference results, a weight parameter is added. The computation of this weighted inference engine is also discussed. In order to test the proposed inference engine, this research also proposes a new method to define membership degrees from statistical data. With this method, the BK subproduct is tested with 3 publicly available data sets. The results are compared. Experimental results show that the extension to interval-valued fuzzy sets and the additional weight parameter improve the quality of inferences. 2015 Thesis NonPeerReviewed application/pdf http://studentsrepo.um.edu.my/11399/1/Lim_Chee_Kau.pdf Lim , Chee Kau (2015) Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau. PhD thesis, University of Malaya. http://studentsrepo.um.edu.my/11399/
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Student Repository
url_provider http://studentsrepo.um.edu.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Lim , Chee Kau
Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
description The studies of fuzzy relations by Bandler and Kohout, which are also known as the BK products, are well known in the literature as tools to study the composition of relations. In the past, BK products, particularly the BK subproduct, gained remarkable success in developing inference engines for numerous applications. Though successful, there are still some limitations. First of all, this research starts with a survey on a set of inference structures formed by the BK subproduct in previous researches. The survey finds shortcomings in some inference structures. With excluding these candidates, a set of robust inference structures are obtained from the analysis. Secondly, with the understanding that the ordinary type-1 fuzzy sets have limited ability in modeling uncertainty, a more general fuzzy set framework is proposed to improve the performance of BK products. Thus, extending BK products to interval-valued fuzzy sets is another contribution of this thesis. Since the subsethood measure is fundamental to the BK products, two interval-valued fuzzy subsethood measures are also developed in this research. Moreover, this research suggests that, among all the features involved in inferences, certain features should have higher influence compared to the others. Therefore, to distinguish the influence of features towards inference results, a weight parameter is added. The computation of this weighted inference engine is also discussed. In order to test the proposed inference engine, this research also proposes a new method to define membership degrees from statistical data. With this method, the BK subproduct is tested with 3 publicly available data sets. The results are compared. Experimental results show that the extension to interval-valued fuzzy sets and the additional weight parameter improve the quality of inferences.
format Thesis
author Lim , Chee Kau
author_facet Lim , Chee Kau
author_sort Lim , Chee Kau
title Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
title_short Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
title_full Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
title_fullStr Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
title_full_unstemmed Interval-valued fuzzy inference systems based on the bandler-kohout subproduct / Lim Chee Kau
title_sort interval-valued fuzzy inference systems based on the bandler-kohout subproduct / lim chee kau
publishDate 2015
url http://studentsrepo.um.edu.my/11399/1/Lim_Chee_Kau.pdf
http://studentsrepo.um.edu.my/11399/
_version_ 1738506479192768512
score 13.211869

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