Cited by 12,187Fuzzy Logic and Control SystemsAdvanced Algebra and LogicMathematical Control Systems and Analysis

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The concept of a linguistic variable and its application to approximate reasoning—I

Zadeh, L.A.·1975·Information Sciences

DOI 10.1016/0020-0255(75)90036-5

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Background
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“Zadeh [1, 2] introduced the concepts of fuzzy sets and fuzzy numbers.”
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“After Zadeh (1965) introduce the ordinary fuzzy sets, numerous extensions have been proposed such as type-2 fuzzy sets (Zadeh, 1975), intuitionistic fuzzy sets (Atanassov,”
Method
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“Values of fuzzy logic are shown as membership in the range of 0–1 (Zadeh 1975).”
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Granular Computing for Machine Learning: Pursuing New Development Horizons
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“Fuzzy sets deliver an important conceptual and algorithmic generalization of sets [3], [18], [19] by admitting a notion of partial membership.”
CI-MM-Dombi operator based on interval type-2 spherical fuzzy set and its applications on sustainable supply chain with risk criteria: using CI-TODIM-MARCOS method
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“Due to this fact, Zadeh (1975) also introduced T2FS to overcome to this type of complex situation.”
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“T1FSs has limited capabilities to model such uncertainties.”
Background
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“In order to express the comparison of different evaluation criteria, representation of the importance weights of different attributes and rankings of alternatives is used as linguistic terms (Zadeh 1975).”
BackgroundMethod
Multi attribute decision-making and interval-valued picture (S, T)-fuzzy graphs
Arif, W., Khan, W. A., Rashmanlou, H., Khan, A., & Muhammad, A. (2023) · Journal of Applied Mathematics and Computation · doi:10.1007/s12190-023-01862-y · Cited by 18
“Definition 3 [2] An IVFS P̄ in T can represented as P̄ = {p, ξP̄ (p) : p ∈ T }, where ξP̄ (p) : T → P([0, 1]) is a closed interval in [0, 1].”
Background
Tech-center location selection by interval-valued spherical fuzzy AHP based MULTIMOORA methodology
Otay, I. (2023) · Soft Computing - A Fusion of Foundations, Methodologies and Applications · doi:10.1007/s00500-023-08082-3 · Cited by 18
“Since 1975, there have been many extensions of Type I fuzzy sets such as Type II fuzzy sets (Zadeh 1975), intuitionistic fuzzy sets (Atanassov 1986), Neutrosophic sets (Smarandache 2005), Hesitant fuzzy sets (Torra 2010), Pythagorean fuzzy sets (Atanassov 1991; Yager 2013), and Spherical fuzzy sets…”
Background
A Gaussian Type-2 Fuzzy Programming Approach for Multicrowd Congestion-Relieved Evacuation Planning
Men, J., Chen, G., Chen, P., & Zhou, L. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2022.3180743 · Cited by 19
“Motivated for these reasons, the concept of a Type-2 fuzzy set (T2-FS) was proposed by Zadeh [37].”
Background
A probabilistic linguistic opinion dynamics method based on the DeGroot model for emergency decision-making in response to COVID-19
Liu, Y., & Yang, Y. (2022) · Computers & industrial engineering · doi:10.1016/j.cie.2022.108677 · Cited by 18

Authors: Zadeh, L. A.
Affiliations: University of California, Berkeley (US)
Corresponding author: Zadeh, L.A.
Venue: Information Sciences
Publisher: Elsevier BV
Published: 1975
Volume: 8
Issue: 3
Pages: 199-249
ISSN: 0020-0255 (ISSN-L)
DOI: 10.1016/0020-0255(75)90036-5
OpenAlex: W4245152641
Cited by: 12,187
References: 48
Citations by year: 2026: 309 · 2025: 516 · 2024: 569 · 2023: 707 · 2022: 682 · 2021: 746 · 2020: 693 · 2019: 759 · 2018: 655 · 2017: 598 · 2016: 551 · 2015: 546 · 2014: 484 · 2013: 437 · 2012: 367
FWCI: 13.65
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/legal/tdmrep-license (tdm)
Locations: Information Sciences (publishedVersion)
Funders: Army Research Office (DA-ARO-D-31-124-7 l-G1 74)
National Science Foundation (GK-VP-610656X3)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Algebra and Logic
Physical Sciences › Computer Science › Artificial Intelligence › Mathematical Control Systems and Analysis
Keywords: linguistic variables, approximate reasoning, fuzzy logic, compatibility function, hedges, linguistic truth values, nonlinear programming, human decision-making, fuzzy sets, artificial intelligence

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