research-article

Interval type-2 fuzzy logic systems: theory and design

Authors:

Qilian Liang,

J. M. MendelAuthors Info & Claims

IEEE Transactions on Fuzzy Systems, Volume 8, Issue 5

Pages 535 - 550

https://doi.org/10.1109/91.873577

Published: 01 October 2000 Publication History

Abstract

We present the theory and design of interval type-2 fuzzy logic systems (FLSs). We propose an efficient and simplified method to compute the input and antecedent operations for interval type-2 FLSs: one that is based on a general inference formula for them. We introduce the concept of upper and lower membership functions (MFs) and illustrate our efficient inference method for the case of Gaussian primary MFs. We also propose a method for designing an interval type-2 FLS in which we tune its parameters. Finally, we design type-2 FLSs to perform time-series forecasting when a nonstationary time-series is corrupted by additive noise where SNR is uncertain and demonstrate an improved performance over type-1 FLSs

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Adnan RKumaravel R(2024)Type - 2 mamdani fuzzy inference system based model for rainfall forecastingJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23582846:2(4791-4802)Online publication date: 14-Feb-2024
https://dl.acm.org/doi/10.3233/JIFS-235828
Liu SOh SPedrycz WYang BWang LYoon J(2024)Reinforced Interval Type-2 Fuzzy Clustering-Based Neural Network Realized Through Attention-Based Clustering Mechanism and Successive LearningIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2023.332119732:3(1208-1222)Online publication date: 1-Mar-2024
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Cartagena OTrovò FSáez D(2024)A multivariate approach for fuzzy prediction interval design and its application for a climatization system forecastingExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124715255:PCOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.eswa.2024.124715
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Interval type-2 fuzzy logic systems: theory and design
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Theory of computation

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cover image IEEE Transactions on Fuzzy Systems

IEEE Transactions on Fuzzy Systems Volume 8, Issue 5

October 2000

162 pages

ISSN:1063-6706

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IEEE Press

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Published: 01 October 2000

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Adnan RKumaravel R(2024)Type - 2 mamdani fuzzy inference system based model for rainfall forecastingJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-23582846:2(4791-4802)Online publication date: 14-Feb-2024
https://dl.acm.org/doi/10.3233/JIFS-235828
Liu SOh SPedrycz WYang BWang LYoon J(2024)Reinforced Interval Type-2 Fuzzy Clustering-Based Neural Network Realized Through Attention-Based Clustering Mechanism and Successive LearningIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2023.332119732:3(1208-1222)Online publication date: 1-Mar-2024
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Cartagena OTrovò FSáez D(2024)A multivariate approach for fuzzy prediction interval design and its application for a climatization system forecastingExpert Systems with Applications: An International Journal10.1016/j.eswa.2024.124715255:PCOnline publication date: 1-Dec-2024
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Abdollahzadeh MPourgholi M(2024)Adaptive fuzzy sliding mode control of magnetic levitation system based on Interval Type-2 Fuzzy Neural Network Identification with an Extended Kalman–Bucy filterEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107645130:COnline publication date: 1-Apr-2024
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