Geometric Type-1 and Type-2 Fuzzy Logic Systems
Abstract
This paper presents a novel approach to the representation of type-1 and type-2 fuzzy sets utilising computational geometry. To achieve this our approach borrows ideas from the field of computational geometry and applies these techniques in the novel setting of fuzzy logic. We provide new algorithms for various operations on type-1 and type-2 fuzzy sets and for defuzzification. Results of experiments indicate that this approach reduces the execution speed of these operations
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Existing fuzzy logic methods are often tailored for single data sources, rendering them ineffective at integrating data from multiple sensors, which limits their applicability in real-time decision-making.
“Existing methods are often tailored for single data sources, rendering them ineffective at integrating data from multiple sensors, which limits their applicability in real-time decision-making22.”
From Intelligent evaluation of coal mine solid filling effect using fuzzy logic and improved D-S evidence theory (2025) · cites this paper as [22]
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Zhang, Z., Yang, S., & Liu, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-88913-5
- Authors
- Coupland, S., & John, R.
- Affiliations
- De Montfort University (GB)
- ORCID
- John, Robert
- Venue
- IEEE Transactions on Fuzzy Systems
- Published
- 2007-02
- Volume
- 15
- Issue
- 1
- Pages
- 3-15
- ISSN
- 1063-6706 (ISSN-L)
- OpenAlex
- W2063928388
- Cited by
- 316
- References
- 0
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 7 · 2023: 11 · 2022: 11 · 2021: 13 · 2020: 8 · 2019: 20 · 2018: 14 · 2017: 20 · 2016: 17 · 2015: 17 · 2014: 27 · 2013: 29 · 2012: 26
- FWCI
- 24.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Fuzzy Systems (publishedVersion)
- DMU Open Research Archive (De Montfort University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Algebra and Logic
- Social Sciences › Decision Sciences › Management Science and Operations Research › Fuzzy and Soft Set Theory
- Keywords
- type-1 fuzzy sets, type-2 fuzzy sets, computational geometry, fuzzy set representation, fuzzy set operations, defuzzification, fuzzy systems, computational efficiency
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