Results for ' fuzzy logic'

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  1.  22
    Fuzzy logic: applications in artificial intelligence, big data, and machine learning.Lefteri H. Tsoukalas - 2023 - New York: McGraw Hill.
    This hands-on guide offers clear explanations of fuzzy logic along with practical uses and detailed examples. Written by an award-winning engineer and experienced author, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and skills in students and professionals alike. Inside, you will discover how to apply fuzzy logic and migrate to a new man-machine relationship in the context of pervasive digitization and big data across emerging technologies. (...)
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  2.  49
    Why Fuzzy Logic?Petr Hájek - 2002 - In Dale Jacquette (ed.), A Companion to Philosophical Logic. Malden, MA, USA: Wiley-Blackwell. pp. 595–605.
    This chapter contains sections titled: Origin Many‐Valued Logic Fuzzy Logic in a Broad and Narrow Sense The Basic Fuzzy Propositional Calculus The Basic Fuzzy Predicate Calculus Similarity The Liar and Dequotation Very True Probability Conclusion.
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  3. Fuzzy logic and approximate reasoning.L. A. Zadeh - 1975 - Synthese 30 (3-4):407-428.
    The term fuzzy logic is used in this paper to describe an imprecise logical system, FL, in which the truth-values are fuzzy subsets of the unit interval with linguistic labels such as true, false, not true, very true, quite true, not very true and not very false, etc. The truth-value set, , of FL is assumed to be generated by a context-free grammar, with a semantic rule providing a means of computing the meaning of each linguistic truth-value (...)
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  4.  48
    Residuated fuzzy logics with an involutive negation.Francesc Esteva, Lluís Godo, Petr Hájek & Mirko Navara - 2000 - Archive for Mathematical Logic 39 (2):103-124.
    Residuated fuzzy logic calculi are related to continuous t-norms, which are used as truth functions for conjunction, and their residua as truth functions for implication. In these logics, a negation is also definable from the implication and the truth constant $\overline{0}$ , namely $\neg \varphi$ is $\varphi \to \overline{0}$. However, this negation behaves quite differently depending on the t-norm. For a nilpotent t-norm (a t-norm which is isomorphic to Łukasiewicz t-norm), it turns out that $\neg$ is an involutive (...)
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  5.  74
    Mathematical fuzzy logics.Siegfried Gottwald - 2008 - Bulletin of Symbolic Logic 14 (2):210-239.
    The last decade has seen an enormous development in infinite-valued systems and in particular in such systems which have become known as mathematical fuzzy logics. The paper discusses the mathematical background for the interest in such systems of mathematical fuzzy logics, as well as the most important ones of them. It concentrates on the propositional cases, and mentions the first-order systems more superficially. The main ideas, however, become clear already in this restricted setting.
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  6.  91
    Substructural Fuzzy Logics.George Metcalfe & Franco Montagna - 2007 - Journal of Symbolic Logic 72 (3):834 - 864.
    Substructural fuzzy logics are substructural logics that are complete with respect to algebras whose lattice reduct is the real unit interval [0.1]. In this paper, we introduce Uninorm logic UL as Multiplicative additive intuitionistic linear logic MAILL extended with the prelinearity axiom ((A → B) ∧ t) ∨ ((B → A) ∧ t). Axiomatic extensions of UL include known fuzzy logics such as Monoidal t-norm logic MTL and Gödel logic G, and new weakening-free logics. (...)
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  7. Fuzzy Logic and Higher-Order Vagueness.Nicholas J. J. Smith - 2011 - In Petr Cintula, Chris Fermüller, Lluis Godo & Petr Hájek (eds.), Logical Models of Reasoning with Vague Information. pp. 1--19.
    The major reason given in the philosophical literature for dissatisfaction with theories of vagueness based on fuzzy logic is that such theories give rise to a problem of higherorder vagueness or artificial precision. In this paper I first outline the problem and survey suggested solutions: fuzzy epistemicism; measuring truth on an ordinal scale; logic as modelling; fuzzy metalanguages; blurry sets; and fuzzy plurivaluationism. I then argue that in order to decide upon a solution, we (...)
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  8.  71
    Fuzzy logic and arithmetical hierarchy III.Petr Hájek - 2001 - Studia Logica 68 (1):129-142.
    Fuzzy logic is understood as a logic with a comparative and truth-functional notion of truth. Arithmetical complexity of sets of tautologies and satisfiable sentences as well of sets of provable formulas of the most important systems of fuzzy predicate logic is determined or at least estimated.
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  9.  49
    Fuzzy Logic and Strategic Management: An Application of Ragin’s Fuzzy-Set Methods.Özlem Öz - 2005 - Philosophy of Management 5 (1):55-66.
    The main purpose of this article is to bring Ragin’s recent methodological contributions, which build on ideas borrowed from fuzzy logic, to the attention of management scholars. To demonstrate the possible use of the techniques developed by Ragin in management research, three specific examples for their likely applications are presented: the replications of Porter’s diamond framework for Turkey, Greece and Canada. The article concludes that Ragin’s systematic techniques prove helpful in making explicit the process of comparing qualitative evidence (...)
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  10.  15
    Using fuzzy logic: towards intelligent systems.Jun Yan - 1994 - New York: Prentice-Hall. Edited by Michael Ryan & James Power.
    A clear account of the principles of fuzzy logic-based design, from a computer/electronics engineering perspective. This pedagogical work incorporates current fuzzy logic techniques, emphasizing hardware/software design for fuzzy systems and fuzzy logic development tools.
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  11. Fuzzy logics based on [0,1)-continuous uninorms.Dov Gabbay & George Metcalfe - 2007 - Archive for Mathematical Logic 46 (5-6):425-449.
    Axiomatizations are presented for fuzzy logics characterized by uninorms continuous on the half-open real unit interval [0,1), generalizing the continuous t-norm based approach of Hájek. Basic uninorm logic BUL is defined and completeness is established with respect to algebras with lattice reduct [0,1] whose monoid operations are uninorms continuous on [0,1). Several extensions of BUL are also introduced. In particular, Cross ratio logic CRL, is shown to be complete with respect to one special uninorm. A Gentzen-style hypersequent (...)
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  12.  48
    Δ-core Fuzzy Logics with Propositional Quantifiers, Quantifier Elimination and Uniform Craig Interpolation.Franco Montagna - 2012 - Studia Logica 100 (1-2):289-317.
    In this paper we investigate the connections between quantifier elimination, decidability and Uniform Craig Interpolation in Δ-core fuzzy logics added with propositional quantifiers. As a consequence, we are able to prove that several propositional fuzzy logics have a conservative extension which is a Δ-core fuzzy logic and has Uniform Craig Interpolation.
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  13. Fuzzy Logic.Kazem Sadegh-Zadeh - 2011 - In Handbook of Analytic Philosophy of Medicine. Dordrecht, Heidelberg, New York, London: Springer.
    Medical knowledge as well as clinical practice are characterized by inescapable uncertainty. There are many reasons this is the case, but foremost among them is that almost everything in medicine is inevitably vague, be it something linguistic such as the term “illness”, or something extra-linguistic such as the condition referred to as illness. If we ask ourselves, then, what the term “illness” means exactly, on the one hand; and how we may precisely delimit the condition illness, on the other; we (...)
     
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  14.  54
    Fuzzy logics – quantitatively.Zofia Kostrzycka & Marek Zaionc - 2023 - Journal of Applied Non-Classical Logics 34 (1):97-132.
    The Gödel–Dummett logic and Łukasiewicz one are two main many-valued logics used by the fuzzy logic community. Our goal is a quantitative comparison of these two. In this paper, we will mostly consider the 3-valued Gödel–Dummett logic as well as the 3-valued Łukasiewicz one. We shall concentrate on their implicational-negation fragments which are limited to formulas formed with a fixed finite number of variables. First, we investigate the proportion of the number of true formulas of a (...)
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  15.  27
    Mathematics Behind Fuzzy Logic.Esko Turunen - 1999 - Physica-Verlag Heidelberg.
    Many results in fuzzy logic depend on the mathematical structure the truth value set obeys. In this textbook the algebraic foundations of many-valued and fuzzy reasoning are introduced. The book is self-contained, thus no previous knowledge in algebra or in logic is required. It contains 134 exercises with complete answers, and can therefore be used as teaching material at universities for both undergraduated and post-graduated courses. Chapter 1 starts from such basic concepts as order, lattice, equivalence (...)
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  16.  7
    Fuzzy Logics in Theories of Vagueness.Nicholas J. J. Smith - 2015 - In Petr Cintula, Christian Fermüller & Carles Noguera (eds.), Handbook of Mathematical Fuzzy Logic - Volume 3. College Publications.
  17. Adaptive fuzzy logics for contextual hedge interpretation.Stephan der Waart van Gulivank - 2009 - Journal of Logic, Language and Information 18 (3).
    The article presents several adaptive fuzzy hedge logics . These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically , strictly speaking or loosely speaking , or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information (...)
     
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  18.  29
    ‎Proof Theory for Fuzzy Logics.George Metcalfe, Nicola Olivetti & Dov M. Gabbay - 2008 - Dordrecht, Netherland: Springer.
    Fuzzy logics are many-valued logics that are well suited to reasoning in the context of vagueness. They provide the basis for the wider field of Fuzzy Logic, encompassing diverse areas such as fuzzy control, fuzzy databases, and fuzzy mathematics. This book provides an accessible and up-to-date introduction to this fast-growing and increasingly popular area. It focuses in particular on the development and applications of "proof-theoretic" presentations of fuzzy logics; the result of more than (...)
  19.  54
    Fuzzy logic and nursing.Eun-Ok Im & Wonshik Chee - 2003 - Nursing Philosophy 4 (1):53-60.
    In empiricism, there are only two answers for a question: black or white. Yet, subjective meanings of human behaviours and responses toward health and illness cannot be simply explained with black and white. Gray zones are needed because they are characterized by complexity and require a contextual understanding. In this paper, we present and suggest fuzzy logic as an example of theoretical bases that help transcend the conflicts between objectivity and subjectivity, respect gray zones between black and white (...)
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  20. Fuzzy logic theory and applications: Part I and Part II.Lotfi A. Zadeh - 2018 - New Jersey: World Scientific. Edited by R. A. Aliev.
    part 1. Fuzzy logic theory 1 -- part 2. Applications and advanced topics of fuzzy logic.
     
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  21.  12
    Fuzzy logic and restricted quantifiers.James D. McCawley - 1980 - In Stig Kanger & Sven Öhman (eds.), Philosophy and Grammar. Reidel. pp. 101--118.
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  22.  13
    Fuzzy Logic for Scientific Discoveries in Fuzziological Epistemology.Ahmad Sadeghi - 2024 - International Journal of Philosophy 12 (2):27-37.
    All types of logic started with Aristotle and have been corrected as a traditional, formal, conditional, classical logic and even modern logic carry the main problems of Aristotelian logic. Despite their important differences, because of these core commonalities they are all called Classical Logic. The fundamental limitations of classical logic make it impossible to advance the knowledge necessary to solve growing human problems. All human knowledge, especially scientific knowledge is based on the logical principles (...)
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  23. Fuzzy logic.Ronald R. Yager - 2003 - In L. Nadel (ed.), Encyclopedia of Cognitive Science. Nature Publishing Group.
     
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  24.  9
    Can Fuzzy Logic Help to Pose Some Problems in the Philosophy of Science?Alejandro Sobrino & Enric Trillas - 1997 - Poznan Studies in the Philosophy of the Sciences and the Humanities 61:277-300.
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  25.  70
    Adaptive fuzzy logics for contextual hedge interpretation.Stephan van der Waart van Gulik - 2009 - Journal of Logic, Language and Information 18 (3):333-356.
    The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning (...)
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  26.  22
    Fuzzy Logic and Mathematics: A Historical Perspective.Radim Bělohlávek, Joseph W. Dauben & George J. Klir - 2017 - Oxford, England and New York, NY, USA: Oxford University Press. Edited by Joseph Warren Dauben & George J. Klir.
    The term "fuzzy logic," as it is understood in this book, stands for all aspects of representing and manipulating knowledge based on the rejection of the most fundamental principle of classical logic---the principle of bivalence. According to this principle, each declarative sentence is required to be either true or false. In fuzzy logic, these classical truth values are not abandoned. However, additional, intermediate truth values between true and false are allowed, which are interpreted as degrees (...)
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  27.  10
    Advances in fuzzy logic: selected papers (with comments) of some Spanish authors.Senén Barro & Alberto Bugarín (eds.) - 1998 - [Santiago de Compostela]: Universidade de Santiago de Compostela.
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  28.  43
    Omitting types in fuzzy logic with evaluated syntax.Petra Murinová & Vilém Novák - 2006 - Mathematical Logic Quarterly 52 (3):259-268.
    This paper is a contribution to the development of model theory of fuzzy logic in narrow sense. We consider a formal system EvŁ of fuzzy logic that has evaluated syntax, i. e. axioms need not be fully convincing and so, they form a fuzzy set only. Consequently, formulas are provable in some general degree. A generalization of Gödel's completeness theorem does hold in EvŁ. The truth values form an MV-algebra that is either finite or Łukasiewicz (...)
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  29. Fuzzy logic and nursing.Im Eun Ok & S. Wonshik - 2003 - Nursing Philosophy 4 (1).
     
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  30.  75
    Structural Completeness in Fuzzy Logics.Petr Cintula & George Metcalfe - 2009 - Notre Dame Journal of Formal Logic 50 (2):153-182.
    Structural completeness properties are investigated for a range of popular t-norm based fuzzy logics—including Łukasiewicz Logic, Gödel Logic, Product Logic, and Hájek's Basic Logic—and their fragments. General methods are defined and used to establish these properties or exhibit their failure, solving a number of open problems.
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  31. Fuzzy logic: the beauty of unclear and indistinct ideas.Martin Moleski - 1998 - Appraisal 2.
     
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  32.  36
    Fuzzy logic and applications: 5th international workshop, WILF 2003, Naples, Italy, October 9-11, 2003: revised selected papers.V. Di Gesù, F. Masulli & Alfredo Petrosino (eds.) - 2006 - New York: Springer.
    This volume constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Fuzzy Logic and Applications held in Naples, Italy, in October 2003. The 40 revised full papers presented have gone through two rounds of reviewing and revision. All current issues of theoretical, experimental and applied fuzzy logic and related techniques are addressed with special attention to rough set theory, neural networks, genetic algorithms and soft computing. The papers are organized in topical section on (...)
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  33.  46
    (1 other version)On Fuzzy Logic III. Semantical completeness of some many‐valued propositional calculi.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (25‐29):447-464.
  34.  37
    Concepts and Fuzzy Logic.Radim Bělohlávek & George J. Klir (eds.) - 2011 - MIT Press.
    In this work - both psychologists working on concepts and mathematicians working on fuzzy logic - reassess the usefulness of fuzzy logic for the psychology of concepts.
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  35. The application of fuzzy logic to the precautionary principle.Mirit Shamir, Lior Shamir & Mary H. Durfee - 2007 - Artificial Intelligence and Law 15 (4):411-427.
    One of the major problems in the implementation of the precautionary principle in environmental cases is the estimation of the weight of evidence. In this paper we propose a formal method that determines the weight of evidence based on the specific parameters of a given case. The proposed method is based on an artificial intelligence approach called fuzzy logic, which is commonly used as an interface between logic and human perception, and often applied to computer-based complex decision (...)
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  36.  93
    Fuzzy Logic Programming and Fuzzy Control.Giangiacomo Gerla - 2005 - Studia Logica 79 (2):231-254.
    We show that it is possible to base fuzzy control on fuzzy logic programming. Indeed, we observe that the class of fuzzy Herbrand interpretations gives a semantics for fuzzy programs and we show that the fuzzy function associated with a fuzzy system of IF-THEN rules is the fuzzy Herbrand interpretation associated with a suitable fuzzy program.
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  37.  71
    Mathematical Fuzzy Logic – What It Can Learn from Mostowski and Rasiowa.Petr Hájek - 2006 - Studia Logica 84 (1):51-62.
    Important works of Mostowski and Rasiowa dealing with many-valued logic are analyzed from the point of view of contemporary mathematical fuzzy logic.
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  38. Some notes concerning fuzzy logics.Charles Grady Morgan & Francis Jeffry Pelletier - 1977 - Linguistics and Philosophy 1 (1):79 - 97.
    Fuzzy logics are systems of logic with infinitely many truth values. Such logics have been claimed to have an extremely wide range of applications in linguistics, computer technology, psychology, etc. In this note, we canvass the known results concerning infinitely many valued logics; make some suggestions for alterations of the known systems in order to accommodate what modern devotees of fuzzy logic claim to desire; and we prove some theorems to the effect that there can be (...)
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  39. Fuzzy logic: A key to shared wisdom.Vladimir Dimitrov - unknown
    The ancient mythology could serve as an effective medium for metaphorically conveying complex concepts and principles to a broad spectrum of people. In this paper we show how the fuzzy logic approach can be used to translate the metaphoric language of ancient myths and legends into a 'soft' scientific paradigm which helps us to understand better the social complexity of our time.
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  40.  14
    Introduction to fuzzy logic.James K. Peckol - 2021 - Hoboken, NJ: Wiley.
    Fuzzy logic is finding increased application in the control of real-world processes and in the work with and the manipulation of inexact knowledge. Two of the major attractions of fuzzy logic are: it permits one to express problems in (familiar) linguistic terms and it can be applied where the numerical mathematical model of a system may be too complex or impossible to build using conventional techniques. This book, written in an easily accessible style, assumes that students (...)
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  41.  32
    Strict core fuzzy logics and quasi-witnessed models.Marco Cerami & Francesc Esteva - 2011 - Archive for Mathematical Logic 50 (5-6):625-641.
    In this paper we prove strong completeness of axiomatic extensions of first-order strict core fuzzy logics with the so-called quasi-witnessed axioms with respect to quasi-witnessed models. As a consequence we obtain strong completeness of Product Predicate Logic with respect to quasi-witnessed models, already proven by M.C. Laskowski and S. Malekpour in [19]. Finally we study similar problems for expansions with Δ, define Δ-quasi-witnessed axioms and prove that any axiomatic extension of a first-order strict core fuzzy logic, (...)
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  42.  57
    Fuzzy logic and arithmetical hierarchy, II.Petr Hájek - 1997 - Studia Logica 58 (1):129-141.
    A very simple many-valued predicate calculus is presented; a completeness theorem is proved and the arithmetical complexity of some notions concerning provability is determined.
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  43.  11
    Ai Development and the ‘Fuzzy Logic' of Chinese Cyber Security and Data Laws.Max Parasol - 2021 - Cambridge University Press.
    The book examines the extent to which Chinese cyber and network security laws and policies act as a constraint on the emergence of Chinese entrepreneurialism and innovation. Specifically, how the contradictions and tensions between data localisation laws affect innovation in artificial intelligence. The book surveys the globalised R&D networks, and how the increasing use of open-source platforms by leading Chinese AI firms during 2017–2020, exacerbated the apparent contradiction between Network Sovereignty and Chinese innovation. The drafting of the Cyber Security Law (...)
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  44. An introduction to fuzzy logic for practical applications.Kazuo Tanaka - 1997 - New York: Springer.
    Fuzzy logic has become an important tool for a number of different applications ranging from the control of engineering systems to artificial intelligence. In this concise introduction, the author presents a succinct guide to the basic ideas of fuzzy logic, fuzzy sets, fuzzy relations, and fuzzy reasoning, and shows how they may be applied. The book culminates in a chapter which describes fuzzy logic control: the design of intelligent control systems using (...)
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  45. Fuzzy logic: Mathematical tools for approximate reasoning.Giangiacomo Gerla - 2003 - Bulletin of Symbolic Logic 9 (4):510-511.
     
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  46.  13
    Involutive Weak u-associative Fuzzy Logic WAuIBUL.Eunsuk Yang - 2024 - CHUL HAK SA SANG - Journal of Philosophical Ideas 92 (92):71-89.
    An involutive micanorm-based logic with a weak form of associativity is introduced and its finite standard completeness is addressed. More precisely, we first introduce the logic WAuIBUL as a [0, u]-continuous wau-uninorm analogue of the involutive logic IBUL. We next discuss its algebraic semantics. We then introduce involutive wau-uninorms as involutive uninorms with weak u-associativity in place of associativity and deal with related properties. We last provide finite strong standard completeness for WAuIBUL using a construction of Yang-style. (...)
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  47.  8
    Fuzzy logic-based material selection and synthesis.Mustafa B. Babanli - 2018 - New Jersey: World Scientific.
    This unique compendium presents a comprehensive and self-contained theory of material development under imperfect information and its applications. The book describes new approaches to synthesis and selection of materials with desirable characteristics. Such approaches provide the ability of systematic and computationally effective analysis in order to predict composition, structure and related properties of new materials. The volume will be a useful advanced textbook for graduate students. It is also suitable for academicians and practitioners who wish to have fundamental models in (...)
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  48.  29
    An Extension Principle for Fuzzy Logics.Giangiacomo Gerla - 1994 - Mathematical Logic Quarterly 40 (3):357-380.
    Let S be a set, P the class of all subsets of S and F the class of all fuzzy subsets of S. In this paper an “extension principle” for closure operators and, in particular, for deduction systems is proposed and examined. Namely we propose a way to extend any closure operator J defined in P into a fuzzy closure operator J* defined in F. This enables us to give the notion of canonical extension of a deduction system (...)
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  49.  6
    Adaptive Fuzzy Logics for Contextual Hedge Interpretation.Stephan Waart van Gulik - 2009 - Journal of Logic, Language and Information 18 (3):333-356.
    The article presents several adaptive fuzzy hedge logics. These logics are designed to perform a specific kind of hedge detection. Given a premise set Γ that represents a series of communicated statements, the logics can check whether some predicate occurring in Γ may be interpreted as being (implicitly) hedged by technically, strictly speaking or loosely speaking, or simply non-hedged. The logics take into account both the logical constraints of the premise set as well as conceptual information concerning the meaning (...)
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  50.  95
    On Fuzzy Logic I Many‐valued rules of inference.Jan Pavelka - 1979 - Mathematical Logic Quarterly 25 (3-6):45-52.
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