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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“In 1975, Zadeh (1975) introduced the notion of T2FS and type-2 fuzzy logic system (T2FLS) that have the potential of performing better than T1FSs and type-1 logic systems in situations characterized by lots of uncertainties (Zadeh, 1975; Mendel et al., 2006).”
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A multi-criteria decision-making framework for electric vehicle supplier selection of government agencies and public bodies in China
Wei, Q., & Zhou, C. (2022) · Environmental science and pollution research international · doi:10.1007/s11356-022-22783-6 · Cited by 39
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Background
A fuzzy DEMATEL-ANP-VIKOR analytical model for maintenance strategy selection of safety critical assets
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“Definition 1 Zadeh (1975) Let S = { s0, s1, . . . , sg } be a linguistic term set (LTS), where si i = 0, 1, · · · , g is a linguistic term, and g + 1 is an odd number known as the granularity of S .”
Background
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“Equations (6) and (7) show that ≤ LPFEWA P P P LPFEWA Q Q Q ( , , .”
Background
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“Fuzzy inference systems ﬁrstly proposed in Zadeh (1975) have been commonly used.”
Method
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“According to Zadeh, in 1975, fuzzy foundation was developed from Linguistic Variable and its Application to Approximate Reasoning [51].”
Method
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“…of original fuzzy sets, many scholars gradually proposed various forms of fuzzy sets, such as the L-fuzzy sets (Goguen, 1967), type-2 fuzzy sets (Zadeh, 1975), intuitionistic fuzzy sets (Atanassov, 1986), non-stationary fuzzy sets (Garibaldi et al., 2008), hesitant fuzzy sets (Torra, 2010), and…”
Background
On analysis of the fuzzy fractional order Volterra-Fredholm integro-differential equation
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“In this paper we propose a new method, based on the method of fuzzy sets theory [11-13], to evaluate the effectiveness of reforestation in three groups: the dynamics of indicators of the reforestation, the dynamics of the implementation of measures for thinning and information about patrolling the territory of the for…”
BackgroundMethod
Three-way multi-attribute decision-making under the double hierarchy hesitant fuzzy linguistic information system
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“According to Zadeh (1975), a linguistic variable is a quintuple.”
BackgroundMethodInfluential
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Mao, Q.-H., Chen, J.-J., Lv, J., Guo, M., & Xie, P. (2023) · Environmental science and pollution research international · doi:10.1007/s11356-022-25004-2 · Cited by 35
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“People would rather express their preference assessment linguistically, which leads to a model considered to be situated between the binary and the [0,1]-valued preference models [64].”
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Yang, X.-J., Xu, Z., & Xu, J.-K. (2022) · Expert systems with applications · doi:10.1016/j.eswa.2022.118782 · Cited by 35
Novel distance and entropy definitions for linear Diophantine fuzzy sets and an extension of TOPSIS (LDF‐TOPSIS)
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“In order to ease the data collection process, Zadeh (1975) initiated the concept of fuzzy linguistic variables which are designed as words and statements having a computational correspondence.”
Method
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“For uncertain qualitative information, Zadeh (1974) proposed linguistic fuzzy sets, in which qualitative data is collected for further operations.”
BackgroundMethod
An advanced TOPSIS method with new fuzzy metric based on interval type-2 fuzzy sets
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Multiobjective capacitated green vehicle routing problem with fuzzy time-distances and demands split into bags
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“Zadeh (1975a, 1975b, 1975c) defined linguistic variables, fuzzy rules, and relations, with membership values representing the strength of the relation.”
Background
Classical approximation for fuzzy Fredholm integral equation
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Fusion of probabilistic linguistic term sets for enhanced group decision-making: Foundations, survey and challenges
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A novel framework for FMEA using evidential BWM and SMAA-MARCOS method
Ju, Y., Zhao, Q. L., Martínez, L. M., Liang, Y., Dong, J., Dong, P., & Giannakis, M. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.122796 · Cited by 39
Resilient sustainable investment in digital education technology: A stakeholder-centric decision support model under uncertainty
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Assessing Spatial Synergy Between Integrated Urban Rail Transit System and Urban Form: A BULI-Based MCLSGA Model With the Wisdom of Crowds
Chang, J.-P., Chen, Z.-S., Wang, Z.-J., Jin, L., Pedrycz, W., Martínez, L., & Skibniewski, M. (2023) · IEEE transactions on fuzzy systems · doi:10.1109/tfuzz.2022.3185680 · Cited by 34
“Specifically, BULI, as an extension of FLA, can ensure the easiness of outputting the Assess-Inf and the richness of the outputted Assess-Inf; the method for fusing large-scale BULI-based Ind-Assess-Inf, which includes the algorithm for clustering large-scale Ind-Assess-Inf and the method of weighting the clusters, ca…”
MethodInfluential
Risk assessment for circular business models: A fuzzy Delphi study application for composite materials
Tuni, A., Ijomah, W., Gutteridge, F., Mirpourian, M., Pfeifer, S., & Copani, G. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2022.135722 · Cited by 39
Development of prospect theory in decision making with different types of fuzzy sets: A state-of-the-art literature review
Tian, X., Ma, J., Li, L., Xu, Z., & Tang, M. (2022) · Information Sciences · doi:10.1016/j.ins.2022.10.016 · Cited by 34
A new spherical aggregation function with the concept of spherical fuzzy difference for spherical fuzzy EDAS and its application to industrial robot selection
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“Zadeh(1975)introducedamoreelaborateformoffuzzysets,type-2 fuzzysets.”
A methodology for building interval type‐3 fuzzy systems based on the principle of justifiable granularity
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Generalized Type-2 Fuzzy Parameter Adaptation in the Marine Predator Algorithm for Fuzzy Controller Parameterization in Mobile Robots
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“Based on the initial concepts of FS [42,43], interval type-2 fuzzy sets (IT2FS) represent an uncertainty model [44] (see Table 1).”
Background
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“Afterward, Zadeh (1975) developed type-2 fuzzy (T2F) sets (Ucal Sari & Kahraman, 2015).”
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Result
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Background
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Background
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Background
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“…set (T3 FS) [39,40], denoted as 𝐴 (cid:4666)(cid:2871)(cid:4667) , is represented by a trivariate func ‐ tion, called the MF of 𝐴 (cid:4666)(cid:2871)(cid:4667) , in the cartesian product (Equation (3)), where 𝑋 is the universe for the primary variable of 𝐴 (cid:4666)(cid:2871)(cid:4667) , 𝑥 .”
Background
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“Also, the use of fuzzy theory (Zadeh 1965, 1975) in such cases is observed to be useful when the relationship between the existing criteria is uncertain or the relation between them cannot be explicitly stated (Liu et al. 2016; Vinodh et al. 2012).”
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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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