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The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems

The inclusion of footprint of uncertainty (FOU) in Interval Type-2 Fuzzy Logic Systems (IT2FLSs) made them suitable for modelling uncertainty. This paper investigates the impact of FOU size and number of membership functions (MFs) on the model's prediction performance. An IT2FLS trained using a...

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Main Authors: Hassan, S., Khosravi, A., Jaafar, J.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2016
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995673101&doi=10.1109%2fISMSC.2015.7594036&partnerID=40&md5=8254bc1f6f2a13ac50d7001f9c7186f0
http://eprints.utp.edu.my/30905/
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spelling my.utp.eprints.309052022-03-25T07:41:28Z The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems Hassan, S. Khosravi, A. Jaafar, J. The inclusion of footprint of uncertainty (FOU) in Interval Type-2 Fuzzy Logic Systems (IT2FLSs) made them suitable for modelling uncertainty. This paper investigates the impact of FOU size and number of membership functions (MFs) on the model's prediction performance. An IT2FLS trained using a fast learning method is designed here. The uncertainty in data is captured by designing the IT2FLS with different sizes of FOU. The concept of extreme learning machine (ELM) is then used for optimal tuning of IT2FLS consequent parameters. The designed model is applied to the chaotic time series prediction. During simulation it is observed that the increase in FOU size with the increase in number of MFs give better prediction results. © 2015 IEEE. Institute of Electrical and Electronics Engineers Inc. 2016 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995673101&doi=10.1109%2fISMSC.2015.7594036&partnerID=40&md5=8254bc1f6f2a13ac50d7001f9c7186f0 Hassan, S. and Khosravi, A. and Jaafar, J. (2016) The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems. In: UNSPECIFIED. http://eprints.utp.edu.my/30905/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description The inclusion of footprint of uncertainty (FOU) in Interval Type-2 Fuzzy Logic Systems (IT2FLSs) made them suitable for modelling uncertainty. This paper investigates the impact of FOU size and number of membership functions (MFs) on the model's prediction performance. An IT2FLS trained using a fast learning method is designed here. The uncertainty in data is captured by designing the IT2FLS with different sizes of FOU. The concept of extreme learning machine (ELM) is then used for optimal tuning of IT2FLS consequent parameters. The designed model is applied to the chaotic time series prediction. During simulation it is observed that the increase in FOU size with the increase in number of MFs give better prediction results. © 2015 IEEE.
format Conference or Workshop Item
author Hassan, S.
Khosravi, A.
Jaafar, J.
spellingShingle Hassan, S.
Khosravi, A.
Jaafar, J.
The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
author_facet Hassan, S.
Khosravi, A.
Jaafar, J.
author_sort Hassan, S.
title The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
title_short The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
title_full The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
title_fullStr The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
title_full_unstemmed The impact of FOU size and number of MFs on the prediction performance of Interval Type-2 Fuzzy Logic Systems
title_sort impact of fou size and number of mfs on the prediction performance of interval type-2 fuzzy logic systems
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2016
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84995673101&doi=10.1109%2fISMSC.2015.7594036&partnerID=40&md5=8254bc1f6f2a13ac50d7001f9c7186f0
http://eprints.utp.edu.my/30905/
_version_ 1738657173152464896
score 13.160551

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