Interval type-2 intuitionistic fuzzy logic systems - a comparative evaluation

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Eyoh, Imo, John, Robert and de Maere, Geert (2018) Interval type-2 intuitionistic fuzzy logic systems - a comparative evaluation. Communications in Computer and Information Science, 853 . pp. 687-698. ISSN 1865-0929

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Abstract

Several fuzzy modeling techniques have been employed for handling uncertainties in data. This study presents a comparative evaluation of a new class of interval type-2 fuzzy logic system (IT2FLS) namely: interval type-2 intuitionistic fuzzy logic system (IT2IFLS) of Takagi Sugeno-Kang (TSK)-type with classical IT2FLS and its type-1 variant (IFLS). Simulations are conducted using a real-world gas compression system (GCS) dataset. Study shows that the performance of the proposed framework with membership functions (MFs) and non-membership functions (NMFs) that are each intervals is superior to classical IT2FLS with only MFs (upper and lower) and IFLS with MFs and NMFs that are not intervals in this problem domain.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/932842
Additional Information: Eyoh I., John R., De Maere G. (2018) Interval Type-2 Intuitionistic Fuzzy Logic Systems - A Comparative Evaluation. In: Medina J. et al. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations. IPMU 2018. Communications in Computer and Information Science, vol 853. Springer, Cham. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-91473-2_58. 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), 11-15 June 2018, Cádiz, Spain
Keywords: Interval type-2 intuitionistic fuzzy logic systems; Membership functions; Non-membership functions; Decoupled extended Kalman filter
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: 10.1007/978-3-319-91473-2_58
Depositing User: Eprints, Support
Date Deposited: 05 Jun 2018 14:20
Last Modified: 04 May 2020 19:36
URI: https://eprints.nottingham.ac.uk/id/eprint/52253

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