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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“An IFS on X is deﬁned as are the membership and non-membership functions, and the hesitancy degree can be deﬁned as follows: Deﬁnition 2 (Zadeh 1975) Let X be an universe of discourse.”
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“Type-2 fuzzy sets (T2FSs) are an extension of type-1 fuzzy sets (T1FSs) and were initially presented in Zadeh (1975).”
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A family of fuzzy multi-criteria sorting models FTOPSIS-Sort: Features, case study analysis, and the statistics of distinctions
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“Deﬁnition 2.2 ([45]): S = { s 0 , s 1 , . . . , s 2 r } is a ﬁnite and completely ordered LTS with odd cardinality, where r is a nonnegative integer value. s i denotes a linguistic variable and for two arbitrary linguistic variables s i and s j , the following two conditions hold: First, S is an…”
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Background
The Shapley value based on hesitant fuzzy linguistic comprehensive entropy and its application in noncooperative-cooperative biform game
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“The possibility-theoretic framework offers a straightforward marginalization procedure that preserves validity; this is via the extension principle of Zadeh (1975).”
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“A fuzzy number can be decomposed into a-cuts (Zadeh 1975).”
Background
RETRACTED: Properties of interval-valued quadripartitioned neutrosophic graphs with real-life application
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“The FN was introduced by Zadeh (1975) and has been studied in a wide range of applications (Hussain et al. 2018a, b; Hussain et al. 2020; Sohaib et al. 2019).”
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“Degree subjectivity bears some connection to fuzzy sets (Zadeh 1975), which have been applied to linguistic representations (Cock, Bodenhofer, and Kerre 2000).”
Background
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“So Zadeh [1] proposed the linguistic variable (LV) to describe the qualitative information in decision-making problems.”
Background
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“Zadeh, L. Fuzzy Sets*. Inf.”
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“established the fuzzy set theory [1], fuzzy derivative [2] and also introduced the concept of the linguistic approach and its applications in artificial intelligence, decision-making process information retrieval, and economics [3].”
Background
Evaluating and selecting agricultural insurance packages through an AHP-based fuzzy TOPSIS Method
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“Linguistic variable is a very helpful concept for dealing with situations which are too complex or not well-defined to be reasonably described by traditional quantitative expressions (Zadeh, 1965, 1975).”
Background
A hesitant fuzzy linguistic bidirectional projection-regret decision making model
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“Thanks to Zadeh [17], he deﬁned the linguistic variables to denote the qualitative information by mathematical symbols.”
Background
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“The idea of linguistic variables 46 is a fundamental factor for the establishment of the fuzzy set theory.”
Background
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Akram, M., Ullah, I., & Allahviranloo, T. (2022) · Computational and Applied Mathematics · doi:10.1007/s40314-021-01756-4 · Cited by 12
“Following the concept of fuzzy sets (Zadeh 1965) and fuzzy numbers (Zadeh 1975), several scholars have contributed in the ﬁeld of fuzzy linear programming problems(FLPPs).”
MethodInfluential
Multi-item two-stage fixed-charge 4DTP with hybrid random type-2 fuzzy variable
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“Many researchers considered the concept of type-2 fuzzy sets introduced by Zadeh (1975).”
BackgroundMethod
A collaborative emergency decision making approach based on BWM and TODIM under interval 2-tuple linguistic environment
Qi, K., Chai, H., Duan, Q.-L., Du, Y., Wang, Q.-S., Sun, J.-H., & Liew, K.-M. (2021) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-021-01412-7 · Cited by 12
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“Our work, therefore, utilizes a rule-based approach inspired by the principles presented in the work of Zadeh [49–51] and the database summarization approach in the work of Kacprzyk et al. [23].”
MethodInfluential
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“Fuzzy sets were first proposed by Zadeh (1965) in order to reduce the uncertainty by modeling verbal expressions or words, while Type 2 fuzzy sets were proposed by Zadeh (1975) again in order to model perceptions (Dereli and Altun, 2013).”
Method
A novel picture fuzzy linguistic Muirhead Mean aggregation operators and their application to multiple attribute decision making
Xian, S.-D., Cheng, Y., & Liu, Z. (2021) · Soft Computing - A Fusion of Foundations, Methodologies and Applications · doi:10.1007/s00500-021-06121-5 · Cited by 12
“In addition, the linguistic elements in S should satisfy the following conditions Herrera et al. (1995); Zadeh (1975): 1) If sa, sb ∈ S and a < b, then sa < sb; 2) There exists the negation operator: neg(sa) = sb, where a = l−1−b; 3) Max(sa, sb) = sa , if sa ≥ sb; 4) Min(sa, sb) = sa , if sa ≤ sb.”
Background
An enhanced even swaps method based on prospect theory with hesitant fuzzy linguistic information and its application to the selection of emergency logistics plans under the COVID-19 pandemic outbreak
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“To describe complex and qualitative information, Zadeh (1975) proposed the concept of linguistic variables whose values are linguistic terms instead of precise numbers. As the decision making problem becomes complex, decision makers might hesitate in multiple linguistic terms when evaluating alternatives. In this rega…”
Background
Sustainable competitiveness evaluation of container liners based on granular computing and social network group decision making
Liu, X., Wang, Y., & Wang, L.-D. (2021) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-021-01325-5 · Cited by 12
“To better express the ambiguity of human beings, such as fast, slow, and fair, Zadeh [16] introduced linguistic variables.”
Background
Sustainable Management of the Supply Chain Based on Fuzzy Logic
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“The same author presents Type-2 fuzzy set (T2FS) (Zadeh 1975) that “is a generalization the ordinary fuzzy set in which the membership value for each member of the set is itself a fuzzy set” (S. Singh and Garg 2017).”
Background
Psychological Response in Fire: A Fuzzy Bayesian Network Approach Using Expert Judgment
Ramli, N., Ghani, N. A., Ahmad, N., & Hashim, I. H. M. (2021) · Fire Technology · doi:10.1007/s10694-021-01106-0 · Cited by 15
An optimal solution of energy scheduling problem based on chance-constraint programming model using Interval-valued neutrosophic constraints
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“As a generalization of fuzzy set, Zadeh introduced the concept of interval-valued fuzzy sets (IVFS) Zadeh (1975) that can deal with the situations where assigning an accurate and precise number to an expert’s outlook is too restrictive and the assignment of interval of values is considered more realistic and practical.”
Method
Oriented Fuzzy Numbers vs. Fuzzy Numbers
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Representation and application of Fuzzy soft sets in type-2 environment
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Complex q-Rung Orthopair Uncertain Linguistic Partitioned Bonferroni Mean Operators with Application in Antivirus Mask Selection
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“In this sense, Zadeh [1] first coined fuzzy sets (FSs) to clarify imprecision and dubiousness during assessment procedures.”
BackgroundInfluential
Failure Mode and Effects Analysis Integrated with Multi-Attribute Decision-Making Methods Under Uncertainty: A Systematic Literature Review
Aleksić, A., Tadić, D., Komatina, N., & Nestić, S. (2025) · Mathematics · doi:10.3390/math13132216 · Cited by 11
A novel Aczel-Alsina aggregation operators based multi-criteria group decision making approach under Hesitant fuzzy set for the selection of best brand in Educational Institution
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Robust adaptive DC-voltage regulator design for ultra-lift Luo converter using PD interval type-2 TSK fuzzy controller
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Failure Mode and Effect Analysis Using Interval Type-2 Fuzzy and Multiple-Criteria Decision-Making Methods
Liou, J. J. H., Guo, B. H. T., Huang, S.-W., & Yang, Y.-T. (2024) · Mathematics · doi:10.3390/math12243931 · Cited by 11
“In 1965, Lot ﬁ A. Zadeh introduced the Type-1 Fuzzy Set [24] and in 1975, he proposed the Type-2 Fuzzy Set [25].”
Prioritizing Resource and Policy Barriers to Post-Disaster Recovery in Pakistan: A Multi-Expert Fermatean Fuzzy AHP Analysis
Khan, A., Shah, A. A., Alotaibi, B. A., & Khan, I. (2024) · Sustainability · doi:10.3390/su162310414 · Cited by 11
A quantum probability theory-based method for heterogeneous multi-criteria group decision making with incomplete probabilistic linguistic preference relations considering the interference effect among decision makers
Yan, J., Dong, J.-Y., Wan, S., & Gao, Y. (2024) · Journal of the Operational Research Society · doi:10.1080/01605682.2024.2417726 · Cited by 11
“Zadeh (1975) first defined the linguistic term set (LTS) and developed a fuzzy linguistic method.”
A hybrid-fuzzy-decision-making framework for digital technologies selection
Alaoui, Y. L., Gallab, M., Tkiouat, M., & Nardo, M. D. D. (2024) · Discover Applied Sciences · doi:10.1007/s42452-024-06229-x · Cited by 11
“Zadeh in [57] introduces the notion of an interval-valued fuzzy set, where the membership degree is depicted as an interval rather than a single point within the [0, 1] range.”
Parametric Optimization for Fully Fuzzy Linear Programming Problems with Triangular Fuzzy Numbers
Bhowmick, A., Chakraverty, S., & Chatterjee, S. (2024) · Mathematics · doi:10.3390/math12193051 · Cited by 11
Integrated project delivery (IPD) capabilities on reducing claims in urban underground projects: A hybrid FAHP-FTOPSIS approach
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Interval-valued bipolar complex fuzzy soft sets and their applications in decision making
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Multi-criteria group decision-making for evaluating efficient and smart mobility sharing systems using Pythagorean fuzzy rough numbers
Akram, M., Zahid, S., & Al-kenani, A. (2024) · Granular Computing · doi:10.1007/s41066-024-00466-6 · Cited by 11
“To provide a mathematical representation for dealing with imprecise and uncertain quantities, many tools were developed, such as fuzzy numbers, triangular fuzzy numbers, triangular Pythagorean fuzzy numbers etc. (Zadeh 1975; Luqman et al. 2021).”
Probabilistic Linguistic Petri Nets for Knowledge Representation and Acquisition With Dynamic Consensus Reaching Process
Shi, H., Yu, Y.-X., Liu, R., & Liu, H.-C. (2024) · IEEE transactions on fuzzy systems · doi:10.1109/tfuzz.2023.3347436 · Cited by 11
“The pioneering work was done by Zadeh [47], in which the concept of linguistic variables was introduced.”
Background
Scenario analysis of local storylines to represent uncertainty in complex human-water systems
Alizadeh, M. R., Adamowski, J., & Inam, A. (2024) · Journal of Hydrology · doi:10.1016/j.jhydrol.2024.131186 · Cited by 11
A novel probabilistic q-rung orthopair linguistic neutrosophic information-based method for rating nanoparticles in various sectors
Wahab, A., Ali, J., Riaz, M. B., Asjad, M., & Muhammad, T. (2024) · Scientific Reports · doi:10.1038/s41598-024-55649-7 · Cited by 11
“Researchers have proposed a variety of fuzzy set types 13 , intuitionistic fuzzy 14 , hesitant fuzzy 15 , and linguistic variables 16 , to describe and express the confusing and vague information during making decisions situations in order to address these obstacles.”
General strong fuzzy solutions of fuzzy Sylvester matrix equations involving the BT inverse
He, M., Jiang, H.-J., & Liu, X. (2024) · Fuzzy Sets Syst. · doi:10.1016/j.fss.2024.108862 · Cited by 11
Time-sequential probabilistic fermatean hesitant approach in multi-objective green solid transportation problems for sustainable enhancement
Chaudhary, S., Kumar, T., Yadav, H., Malik, A. K., & Sharma, M. K. (2024) · Alexandria Engineering Journal · doi:10.1016/j.aej.2023.12.045 · Cited by 11
An integrated GBWM-PROMETHEE-CLOUD & MCGP model for green supplier selection and order allocation (GSSOA) in an oil refinery
Goudarzi, A., & Gholamian, M. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2024.140782 · Cited by 11
A cloud service composition method using a fuzzy-based particle swarm optimization algorithm
Nazif, H., Nassr, M., Al-Khafaji, H. M. R., Navimipour, N. J., & Unal, M. (2023) · Multimedia tools and applications · doi:10.1007/s11042-023-17719-2 · Cited by 11
A novel probabilistic linguistic decision-making model based on discrete evidence fusion and attribute weight optimization
Xue, S., Yang, Y., & Deng, X. (2023) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2023.106706 · Cited by 11
Pre-earthquake fuzzy logic-based rapid hazard assessment of reinforced concrete buildings
Mangır, A., & Okumuş, V. (2023) · Case Studies in Construction Materials · doi:10.1016/j.cscm.2023.e02534 · Cited by 11
Development of hamming and hausdorff distance metrics for cubic intuitionistic fuzzy hypersoft set in cement storage quality control: Development and evaluation
Saeed, M., Saeed, M., Khalid, M., & Mekawy, I. (2023) · PLoS ONE · doi:10.1371/journal.pone.0291817 · Cited by 11
“The concept of FS was then extended to interval-valued fuzzy sets (IVFS) by Zadeh in 1975 [4].”
A MAGDM model based on 2-tuple linguistic variables and power Hamacher aggregation operators for optimal selection of digital marketing strategies
Naz, S., Fatima, S. S., Butt, S. A., & Tabassum, N. (2023) · Granular Computing · doi:10.1007/s41066-023-00408-8 · Cited by 11
“Zadeh (1975a) introduced the ﬁrst-ever fuzzy set (FS) with a single membership degree (MD) to address fuzzy problems faced by decision-makers (DMs) in real-world situations.”
BackgroundMethod
A hybrid deep learning framework for automated visual image classification using EEG signals
Ahmadieh, H., Gassemi, F., & Moradi, M. H. (2023) · Neural Computing and Applications · doi:10.1007/s00521-023-08870-w · Cited by 12
“Zadeh introduced type-2 fuzzy sets as the development of type-1 fuzzy sets [33].”
Coming to Consensus on Classification in Flexible Linguistic Preference Relations: The Role of Personalized Individual Semantics
Zhu, W., Zhang, H.-J., & Xiao, J. (2023) · Group Decision and Negotiation · doi:10.1007/s10726-023-09841-1 · Cited by 11
“Due to the complexity of problems as well as the constraints of personal knowledge, it is natural and convenient for decision makers to use linguistic approaches to provide their preferences, which results in the linguistic GDM problem (Zadeh 1975).”
Background
Verification of collision avoidance algorithms in open sea and full visibility using fuzzy logic
Nguyen, D., Trodahl, M., Pedersen, T., & Bakdi, A. (2023) · Ocean Engineering · doi:10.1016/j.oceaneng.2023.114455 · Cited by 11
Pattern recognition and medical diagnosis based on trigonometric similarity measures for bipolar complex fuzzy soft sets
Mahmood, T., Jaleel, A., & Rehman, U. U. (2023) · Soft Computing - A Fusion of Foundations, Methodologies and Applications · doi:10.1007/s00500-023-08176-y · Cited by 11
“Due to certain restrictions and drawbacks, numerous scholars modiﬁed the conception of FSs like interval-valued FSs (IVFSs) (Zadeh 1975), intuitionistic FSs (IFSs) (Atanassov 1999), T-spherical FSs (Shen et al. 2022), etc.”
Background
A hybrid DEMATEL-COPRAS method using interval-valued probabilistic linguistic term set for sustainable hydrogen fuel cell supplier of new energy vehicles
Mao, Q.-H., Chen, J.-J., Lv, J., Guo, M., & Tian, M. (2023) · Environmental science and pollution research international · doi:10.1007/s11356-023-27470-8 · Cited by 11
“To better handle this situation, Zadeh (1975) first put forward the concept of linguistic variables instead of crisp numbers to describe and show the qualitative evaluation information for solving the MCDM problems.”
Background
Hybrid computer aided diagnostic system designs for screen film mammograms using DL ‐based feature extraction and ML ‐based classifiers
Rani, J., Singh, J., & Virmani, J. (2023) · Expert Systems · doi:10.1111/exsy.13309 · Cited by 13
“Thereby neural (Cetisli, 2010a, 2010b; Manogaran et al., 2018; Zadeh et al., 1975a, 1975b, 1975c).”
A two-stage system proposal based on a type-2 fuzzy logic system for ergonomic control of classrooms and offices
Erozan, I., Özel, E., & Erozan, D. (2023) · Engineering applications of artificial intelligence · doi:10.1016/j.engappai.2023.105854 · Cited by 11
Ranking of Service Quality Solution for Blended Design Teaching Using Fuzzy ANP and TOPSIS in the Post-COVID-19 Era
Lin, C., Chen, J.-J., & Ma, Y.-Y. (2023) · Mathematics · doi:10.3390/math11051255 · Cited by 11
Analysis of cybercrimes and security in FinTech industries using the novel concepts of interval-valued complex q-rung orthopair fuzzy relations
Nasir, A., Jan, N., Pamucar, D., & Khan, S. (2023) · Expert systems with applications · doi:10.1016/j.eswa.2023.119976 · Cited by 11
Breast cancer treatment planning using a novel spherical fuzzy CRITIC-REGIME
Akdag, H. C., & Menekşe, A. (2023) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-222648 · Cited by 11
“Using fuzzy systems [58], decision experts may convert their linguistic judgments into numerical values and deal with the inherent uncertainties that come with such assessments.”
A Credibility and Strategic Behavior Approach in Hesitant Multiple Criteria Decision-Making With Application to Sustainable Transportation
Santos-Arteaga, F., Caprio, D. D., Tavana, M., & Tena, E. (2023) · IEEE transactions on fuzzy systems · doi:10.1109/tfuzz.2022.3188875 · Cited by 11
“One of the most recent developments is given by HFSs where a finite set of hesitant fuzzy elements (HFEs) defined within [0, 1] is used to describe the membership degree of the hesitation expressed by DMs. Hybrid models composed of FSs, IFSs, and HFSs and different variants of the latter HFSs have been recently develo…”
BackgroundInfluential
A fuzzy adaptive metaheuristic algorithm for identifying sustainable, economical, and earthquake-resistant reinforced concrete cantilever retaining walls
Keivanian, F., Chiong, R., Kashani, A. R., & Gandomi, A. H. (2023) · Journal of Computational Science · doi:10.1016/j.jocs.2023.101978 · Cited by 12
Comparing a Fuzzy Hybrid Approach with Invariant MGCFA to Study National Identity
Martı́n, J. C., & Indelicato, A. (2023) · Applied Sciences · doi:10.3390/app13031657 · Cited by 10
Adaptive Bezier Curve-based Membership Function formulation scheme for Interpretable Edge Detection
Madhu, C., & SudhakarM., S. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109968 · Cited by 11
Extended PROMETHEE approach with 2‐tuple linguistic m‐polar fuzzy sets for selection of elliptical cardio machine
Akram, M., Noreen, U., & Pamucar, D. (2022) · Expert Syst. J. Knowl. Eng. · doi:10.1111/exsy.13178 · Cited by 11
“Zadeh (1975a, 1975b, 1975c, 1983) presented remarkable contributions to the linguistic representation of data in decision analysis.”
Background
A Complementary Study on General Interval Type-2 Fuzzy Sets
Hernández, P., Cubillo, S., & Torres-Blanc, C. (2022) · IEEE transactions on fuzzy systems · doi:10.1109/tfuzz.2022.3167140 · Cited by 11
“The algebraic operations (join, meet, and complementation) on M , given in Deﬁnition 4, were determined from the Zadeh’s Extension Principle (see [25] and [26]).”
Method
Geometric linguistic scale and its application in multi-attribute decision-making for green agricultural product supplier selection
Wu, X., & Liao, H.-C. (2022) · Fuzzy Sets Syst. · doi:10.1016/j.fss.2022.08.026 · Cited by 11
Extension of Restricted Equivalence Functions and Similarity Measures for Type-2 Fuzzy Sets
de Miguel, L., Santiago, R., Wagner, C., Garibaldi, J., Takác̆, Z., Hierro, A., & Bustince, H. (2022) · IEEE transactions on fuzzy systems · doi:10.1109/tfuzz.2021.3136349 · Cited by 11
“In this paper, we work with Type-2 FSs (T2FS) as originally introduced by Zadeh in [35].”
Method
Robot Selection Using An Integrated MAGDM Model Based on ELECTRE Method and Linguistic q-Rung Orthopair Fuzzy Information
Bao, H., & Shi, X. (2022) · Mathematical Problems in Engineering · doi:10.1155/2022/1444486 · Cited by 11
A Novel Description of Some Concepts in Interval-Valued Intuitionistic Fuzzy Graph with an Application
Qiang, X.-L., Kosari, S., Chen, X., Talebi, A., Muhiuddin, G., & Sadati, S. H. (2022) · Advances in Mathematical Physics · doi:10.1155/2022/2412012 · Cited by 11
“Zadeh [2] also introduced the interval-valued fuzzy set (IVFS) in 1975, in which membership degrees were intervals of numbers.”
Background
Fuzzy time series model based on red-black trees for stock index forecasting
Tavares, T. H. B. D. C., Ferreira, B., & Mendes, E. M. A. M. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.109323 · Cited by 11
Qualitative capacities: Basic notions and potential applications
Dubois, D., Faux, F., Prade, H., & Rico, A. (2022) · International Journal of Approximate Reasoning · doi:10.1016/j.ijar.2022.05.009 · Cited by 11
“Very early, Zadeh introduced linguistic scales for evaluation purposes via the use of linguistic variables [82] pertaining to numerical quantities, and later on he introduced the paradigm of computing with words [84].”
Background
AN EXTENSION OF THE MABAC AND OS MODEL USING LINGUISTIC NEUTROSOPHIC NUMBERS: SELECTION OF UNMANNED AIRCRAFT FOR FIGHTING FOREST FIRES
Pamucar, D., Petrovic, I., Ćirović, G., & Stević, Ž. (2022) · Transport · doi:10.3846/transport.2022.16645 · Cited by 11
On the relationship between possibilistic and standard moments of fuzzy numbers
Stoklasa, J., Luukka, P., & Collan, M. (2022) · Journal of Computational and Applied Mathematics · doi:10.1016/j.cam.2022.114276 · Cited by 11
An efficient method for solving neutrosophic Fredholm integral equations of second kind
Moi, S., Biswas, S., & Sarkar, S. P. (2022) · Granular Computing · doi:10.1007/s41066-021-00310-1 · Cited by 11
“Neutrosophic set is the generalization of fuzzy set (Zadeh 1975).”
Background
On union and intersection of type-2 fuzzy sets not expressible by the sup-t-norm extension principle
Wu, X.-X., Chen, G., & Wang, L. (2021) · Fuzzy Sets Syst. · doi:10.1016/j.fss.2021.10.001 · Cited by 11
Proof-of-Concept of a Sensor-Based Evaluation Method for Better Sensitivity of Upper-Extremity Motor Function Assessment
Lee, S.-H., Hwang, Y., Lee, H.-J., Kim, Y., Ogrinc, M., Burdet, E., & Kim, J. (2021) · Italian National Conference on Sensors · doi:10.3390/s21175926 · Cited by 11
“Importantly, the binary logic was verified by high grading accuracy with the original FM scale [13] and could be applied to continuous scoring through the fuzzy logic approach, such as designing an appropriate fuzzy inference system (FIS) [23,24].”
Method
A type-1 OWA operator for Extended Comparative Linguistic Expressions with Symbolic Translation
He, W., Rodríguez, R. M., Dutta, B., & Martínez, L. (2021) · Fuzzy Sets Syst. · doi:10.1016/j.fss.2021.08.002 · Cited by 11
The integrated PFMEA approach with interval type-2 fuzzy sets and FBWM: A case study in the automotive industry
Komatina, N., Tadić, D., Aleksić, A., & Banduka, N. (2021) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1177/09544070211034799 · Cited by 16
“In the literature, there are many papers where the modeling uncertainty is based on the concept of type-2 fuzzy sets (IT2FSs).(24,27) Handling of uncertainties by using the IT2FNSs demand less computing complexity than IT2FSs so widely used and have been successfully applied in perceptual computing.”
Background

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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