2011 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2011) : El Paso, Texas, USA, 18-20 March 2011 |
Pubbl/distr/stampa | [Place of publication not identified], : IEEE, 2011 |
Disciplina | 511.3/13 |
Soggetto topico |
Soft computing
Neural networks (Computer science) Fuzzy systems Engineering & Applied Sciences Computer Science |
ISBN | 1-61284-967-9 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996206609603316 |
[Place of publication not identified], : IEEE, 2011 | ||
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Lo trovi qui: Univ. di Salerno | ||
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2011 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2011) : El Paso, Texas, USA, 18-20 March 2011 |
Pubbl/distr/stampa | [Place of publication not identified], : IEEE, 2011 |
Disciplina | 511.3/13 |
Soggetto topico |
Soft computing
Neural networks (Computer science) Fuzzy systems Engineering & Applied Sciences Computer Science |
ISBN |
9781612849676
1612849679 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910140988303321 |
[Place of publication not identified], : IEEE, 2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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Concepts and fuzzy logic [[electronic resource] /] / edited by Radim Belohlavek and George J. Klir |
Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, c2011 |
Descrizione fisica | 1 online resource (287 p.) |
Disciplina | 511.3/13 |
Altri autori (Persone) |
BělohlávekRadim
KlirGeorge J. <1932-> |
Soggetto topico |
Fuzzy logic
Concepts |
Soggetto genere / forma | Electronic books. |
ISBN |
0-262-29768-X
1-283-30280-2 9786613302809 0-262-29857-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Contents; Preface; Acknowledgments; Chapter 1. Introduction; Chapter 2. Concepts: A Tutorial; Chapter 3. Fuzzy Logic: A Tutorial; Chapter 4. "Slow Lettuce": Categories, Concepts, Fuzzy Sets, and Logical Deduction; Chapter 5. Fallacious Perceptions of Fuzzy Logic in the Psychology of Concepts; Chapter 6. Representing Concepts by Fuzzy Sets; Chapter 7. Formal Concept Analysis: Classical and Fuzzy; Chapter 8. Conceptual Combinations and Fuzzy Logic; Chapter 9. Concepts and Natural Language; Chapter 10. Epilogue; Contributors; Glossary of Symbols; Contributors; Index |
Record Nr. | UNINA-9910464764103321 |
Cambridge, Mass., : MIT Press, c2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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Concepts and fuzzy logic / / edited by Radim Belohlavek and George J. Klir |
Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, ©2011 |
Descrizione fisica | 1 online resource (287 p.) |
Disciplina | 511.3/13 |
Altri autori (Persone) |
BělohlávekRadim
KlirGeorge J. <1932-> |
Soggetto topico |
Fuzzy logic
Concepts |
Soggetto non controllato |
COGNITIVE SCIENCES/General
COGNITIVE SCIENCES/Psychology/Cognitive Psychology MATHEMATICS & STATISTICS/General |
ISBN |
0-262-29768-X
1-283-30280-2 9786613302809 0-262-29857-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Contents; Preface; Acknowledgments; Chapter 1. Introduction; Chapter 2. Concepts: A Tutorial; Chapter 3. Fuzzy Logic: A Tutorial; Chapter 4. "Slow Lettuce": Categories, Concepts, Fuzzy Sets, and Logical Deduction; Chapter 5. Fallacious Perceptions of Fuzzy Logic in the Psychology of Concepts; Chapter 6. Representing Concepts by Fuzzy Sets; Chapter 7. Formal Concept Analysis: Classical and Fuzzy; Chapter 8. Conceptual Combinations and Fuzzy Logic; Chapter 9. Concepts and Natural Language; Chapter 10. Epilogue; Contributors; Glossary of Symbols; Contributors; Index |
Record Nr. | UNINA-9910789461503321 |
Cambridge, Mass., : MIT Press, ©2011 | ||
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Lo trovi qui: Univ. Federico II | ||
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ICHIT 2008 : 2008 International Conference on Convergence and Hybrid Information Technology : proceedings : 28-29 August 2008, Daejeon, Korea |
Pubbl/distr/stampa | [Place of publication not identified], : IEEE Computer Society, 2008 |
Disciplina | 511.3/13 |
Soggetto topico |
Computer systems
Information technology Computer networks Coding theory Fuzzy systems Engineering & Applied Sciences Computer Science |
ISBN | 1-5090-8163-1 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNISA-996198339703316 |
[Place of publication not identified], : IEEE Computer Society, 2008 | ||
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Lo trovi qui: Univ. di Salerno | ||
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ICHIT 2008 : 2008 International Conference on Convergence and Hybrid Information Technology : proceedings : 28-29 August 2008, Daejeon, Korea |
Pubbl/distr/stampa | [Place of publication not identified], : IEEE Computer Society, 2008 |
Disciplina | 511.3/13 |
Soggetto topico |
Computer systems
Information technology Computer networks Coding theory Fuzzy systems Engineering & Applied Sciences Computer Science |
ISBN |
9781509081639
1509081631 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910140029503321 |
[Place of publication not identified], : IEEE Computer Society, 2008 | ||
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Lo trovi qui: Univ. Federico II | ||
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Insight into fuzzy modeling / / Vilém Novák, Irina Perfilieva, and Antonín Dvoŕ̌ák, University of Ostrava, Czech Republic |
Autore | Novák Vilém <1951-> |
Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2016] |
Descrizione fisica | 1 online resource (269 pages) : illustrations (some color) |
Disciplina | 511.3/13 |
Soggetto topico |
Simulation methods
Fuzzy mathematics Fuzzy systems - Mathematical models |
ISBN |
1-119-19320-6
1-119-19319-2 |
Classificazione | TEC008000 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine generated contents note: Preface xv Acknowledgments xvii PART I FUNDAMENTALS OF FUZZY MODELING 1 What is fuzzy modeling 3 1.1 Indeterminacy in human life 3 1.2 Fuzzy modeling: with and without words 6 2 Overview of basic notions 11 2.1 Relations, functions, ordered sets 11 2.2 Fuzzy sets and fuzzy relations 14 2.2.1 The concept of a fuzzy set 15 2.2.2 Operations with fuzzy sets 20 2.2.3 Fuzzy numbers 29 2.2.4 Fuzzy partition and fuzzy covering 33 2.2.5 Cartesian product and fuzzy relations 34 2.2.6 Fuzzy equality and extensional fuzzy sets 41 2.3 Elements of mathematical fuzzy logic 44 2.3.1 Structure of truth degrees in mathematical fuzzy logic 44 2.3.2 Logical inference 47 2.3.3 Formal systems of MFL 48 2.3.4 The concept of fuzzy IF-THEN rule 50 3 Fuzzy IF-THEN rules in approximation of functions 53 3.1 Relational interpretation of fuzzy IF-THEN rules 53 3.1.1 Finite functions and their description 54 3.1.2 Relational interpretation of linguistic descriptions 57 3.1.3 Managing more variables 64 3.2 Approximation of functions using fuzzy IF-THEN rules 64 3.2.1 Defuzzification 64 3.2.2 Fuzzy approximation 67 3.2.3 Construction of approximating function 67 3.2.4 Choosing between DNF and CNF. 74 3.3 Generalized modus ponens and fuzzy functions 77 3.4 TakagiSugeno rules 80 3.4.1 Basic concepts 80 3.4.2 Fuzzy approximation using TSrules 80 3.4.3 Identification of TSrules 84 4 Fuzzy transform 87 4.1 Fuzzy partition 88 4.2 The concept of F-transform 90 4.2.1 Direct F-transform 90 4.2.2 Inverse F-transform 92 4.3 Discrete F-transform 95 4.4 F-transform of functions of two variables 96 4.5 F1transform 98 4.6 Methodological remarks to applications of the F-transform 101 5 Fuzzy natural logic and approximate reasoning 103 5.1 Linguistic semantics and linguistic variable 103 5.1.1 Linguistic variable 104 5.1.2 Intension, context, extension 105 5.1.3 Refined definition of linguistic variable 106 5.2 Theory of evaluative linguistic expressions 108 5.2.1 The concept and structure of evaluative expressions 108 5.2.2 Evaluative linguistic predications 111 5.2.3 Mathematical model of the semantics of evaluative linguistic expressions 113 5.3 Interpretation of fuzzy/linguistic IF-THEN rules 124 5.3.1 Linguistic description 124 5.3.2 Intension of fuzzy/linguistic IF-THEN rules 125 5.4 Approximate reasoning with linguistic information 126 5.4.1 Basic principle of approximate reasoning 126 5.4.2 Perceptionbased logical deduction 127 5.4.3 Formalization of the perceptionbased logical deduction 131 5.4.4 Comparison of two interpretations of fuzzy IF-THEN rules 136 6 Fuzzy cluster analysis 145 6.1 Basic notions 145 6.2 Fuzzy clustering algorithms 147 6.3 The algorithm of fuzzy cmeans 148 6.4 The GustafsonKessel algorithm 151 6.5 How the number of clusters can be determined 152 6.6 Construction of fuzzy rules based on found clusters 153 PART II SELECTED APPLICATIONS 7 Fuzzy/linguistic control and decisionmaking 159 7.1 The principle of fuzzy control 159 7.1.1 Control in a closed feedback loop 161 7.1.2 A general scheme of fuzzy controller 162 7.2 Fuzzy controllers 165 7.2.1 Variables 166 7.2.2 Basic types of classical controllers 167 7.2.3 Basic types of fuzzy controllers 167 7.3 Design of fuzzy/linguistic controller 169 7.3.1 Determination of variables and linguistic context 169 7.3.2 Choosing fuzzy action unit 171 7.3.3 Formation of knowledge base 172 7.3.4 Tuning linguistic description 177 7.4 Learning 180 7.4.1 Modification and learning of linguistic context 180 7.4.2 Learning linguistic description 183 7.4.3 Practical experiences with control using linguistic fuzzy action unit 188 7.5 Decisionmaking using linguistic descriptions 190 7.5.1 Introduction 190 7.5.2 Hierarchy of linguistic descriptions in decisionmaking 191 7.5.3 Demonstration of the decisionmaking methodology using linguistic descriptions 193 8 F-transform in image processing 197 8.1 Image and its basic processing using F-transform 197 8.2 F-transform based image compression and reconstruction 198 8.2.1 Basic principles of image compression 198 8.2.2 Simple F-transform compression 199 8.2.3 Advanced Image Compression 200 8.3 F1transform edge detector 201 8.4 F-transform based image fusion 204 8.4.1 Basic idea of image fusion 204 8.4.2 Simple F-transform based fusion algorithm 205 8.4.3 Complete F-transform based fusion algorithm 207 8.4.4 Enhanced simple fusion algorithm 209 8.5 F-transform based corrupted image reconstruction 211 8.5.1 The reconstruction problem 212 8.5.2 F-transform based reconstruction 212 8.5.3 Demonstration examples 214 9 Analysis and forecasting of time series 219 9.1 Classical vs. fuzzy models of time series 220 9.1.1 Definition of time series 220 9.1.2 Classical models of time series 220 9.1.3 Fuzzy models of time series 221 9.2 Analysis of time series using F-transform 222 9.2.1 Decomposition of time series 222 9.2.2 Extraction of trendcycle and trend using F-transform 224 9.3 Time series forecasting 229 9.3.1 Decomposition of time domain 229 9.3.2 Forecast of trendcycle 230 9.3.3 Forecast of seasonal component 234 9.3.4 Forecast of the whole time series 235 9.4 Characterization of time series in natural language 236 9.4.1 Sentences characterizing trend 236 9.4.2 Automatic generation of sentences characterizing trend 238 9.4.3 Mining information from time series 241 References 245 Index 255. |
Record Nr. | UNINA-9910136529503321 |
Novák Vilém <1951->
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Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2016] | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Insight into fuzzy modeling / / Vilém Novák, Irina Perfilieva, and Antonín Dvoŕ̌ák, University of Ostrava, Czech Republic |
Autore | Novák Vilém <1951-> |
Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2016] |
Descrizione fisica | 1 online resource (269 pages) : illustrations (some color) |
Disciplina | 511.3/13 |
Soggetto topico |
Simulation methods
Fuzzy mathematics Fuzzy systems - Mathematical models |
ISBN |
1-119-19320-6
1-119-19319-2 |
Classificazione | TEC008000 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Machine generated contents note: Preface xv Acknowledgments xvii PART I FUNDAMENTALS OF FUZZY MODELING 1 What is fuzzy modeling 3 1.1 Indeterminacy in human life 3 1.2 Fuzzy modeling: with and without words 6 2 Overview of basic notions 11 2.1 Relations, functions, ordered sets 11 2.2 Fuzzy sets and fuzzy relations 14 2.2.1 The concept of a fuzzy set 15 2.2.2 Operations with fuzzy sets 20 2.2.3 Fuzzy numbers 29 2.2.4 Fuzzy partition and fuzzy covering 33 2.2.5 Cartesian product and fuzzy relations 34 2.2.6 Fuzzy equality and extensional fuzzy sets 41 2.3 Elements of mathematical fuzzy logic 44 2.3.1 Structure of truth degrees in mathematical fuzzy logic 44 2.3.2 Logical inference 47 2.3.3 Formal systems of MFL 48 2.3.4 The concept of fuzzy IF-THEN rule 50 3 Fuzzy IF-THEN rules in approximation of functions 53 3.1 Relational interpretation of fuzzy IF-THEN rules 53 3.1.1 Finite functions and their description 54 3.1.2 Relational interpretation of linguistic descriptions 57 3.1.3 Managing more variables 64 3.2 Approximation of functions using fuzzy IF-THEN rules 64 3.2.1 Defuzzification 64 3.2.2 Fuzzy approximation 67 3.2.3 Construction of approximating function 67 3.2.4 Choosing between DNF and CNF. 74 3.3 Generalized modus ponens and fuzzy functions 77 3.4 TakagiSugeno rules 80 3.4.1 Basic concepts 80 3.4.2 Fuzzy approximation using TSrules 80 3.4.3 Identification of TSrules 84 4 Fuzzy transform 87 4.1 Fuzzy partition 88 4.2 The concept of F-transform 90 4.2.1 Direct F-transform 90 4.2.2 Inverse F-transform 92 4.3 Discrete F-transform 95 4.4 F-transform of functions of two variables 96 4.5 F1transform 98 4.6 Methodological remarks to applications of the F-transform 101 5 Fuzzy natural logic and approximate reasoning 103 5.1 Linguistic semantics and linguistic variable 103 5.1.1 Linguistic variable 104 5.1.2 Intension, context, extension 105 5.1.3 Refined definition of linguistic variable 106 5.2 Theory of evaluative linguistic expressions 108 5.2.1 The concept and structure of evaluative expressions 108 5.2.2 Evaluative linguistic predications 111 5.2.3 Mathematical model of the semantics of evaluative linguistic expressions 113 5.3 Interpretation of fuzzy/linguistic IF-THEN rules 124 5.3.1 Linguistic description 124 5.3.2 Intension of fuzzy/linguistic IF-THEN rules 125 5.4 Approximate reasoning with linguistic information 126 5.4.1 Basic principle of approximate reasoning 126 5.4.2 Perceptionbased logical deduction 127 5.4.3 Formalization of the perceptionbased logical deduction 131 5.4.4 Comparison of two interpretations of fuzzy IF-THEN rules 136 6 Fuzzy cluster analysis 145 6.1 Basic notions 145 6.2 Fuzzy clustering algorithms 147 6.3 The algorithm of fuzzy cmeans 148 6.4 The GustafsonKessel algorithm 151 6.5 How the number of clusters can be determined 152 6.6 Construction of fuzzy rules based on found clusters 153 PART II SELECTED APPLICATIONS 7 Fuzzy/linguistic control and decisionmaking 159 7.1 The principle of fuzzy control 159 7.1.1 Control in a closed feedback loop 161 7.1.2 A general scheme of fuzzy controller 162 7.2 Fuzzy controllers 165 7.2.1 Variables 166 7.2.2 Basic types of classical controllers 167 7.2.3 Basic types of fuzzy controllers 167 7.3 Design of fuzzy/linguistic controller 169 7.3.1 Determination of variables and linguistic context 169 7.3.2 Choosing fuzzy action unit 171 7.3.3 Formation of knowledge base 172 7.3.4 Tuning linguistic description 177 7.4 Learning 180 7.4.1 Modification and learning of linguistic context 180 7.4.2 Learning linguistic description 183 7.4.3 Practical experiences with control using linguistic fuzzy action unit 188 7.5 Decisionmaking using linguistic descriptions 190 7.5.1 Introduction 190 7.5.2 Hierarchy of linguistic descriptions in decisionmaking 191 7.5.3 Demonstration of the decisionmaking methodology using linguistic descriptions 193 8 F-transform in image processing 197 8.1 Image and its basic processing using F-transform 197 8.2 F-transform based image compression and reconstruction 198 8.2.1 Basic principles of image compression 198 8.2.2 Simple F-transform compression 199 8.2.3 Advanced Image Compression 200 8.3 F1transform edge detector 201 8.4 F-transform based image fusion 204 8.4.1 Basic idea of image fusion 204 8.4.2 Simple F-transform based fusion algorithm 205 8.4.3 Complete F-transform based fusion algorithm 207 8.4.4 Enhanced simple fusion algorithm 209 8.5 F-transform based corrupted image reconstruction 211 8.5.1 The reconstruction problem 212 8.5.2 F-transform based reconstruction 212 8.5.3 Demonstration examples 214 9 Analysis and forecasting of time series 219 9.1 Classical vs. fuzzy models of time series 220 9.1.1 Definition of time series 220 9.1.2 Classical models of time series 220 9.1.3 Fuzzy models of time series 221 9.2 Analysis of time series using F-transform 222 9.2.1 Decomposition of time series 222 9.2.2 Extraction of trendcycle and trend using F-transform 224 9.3 Time series forecasting 229 9.3.1 Decomposition of time domain 229 9.3.2 Forecast of trendcycle 230 9.3.3 Forecast of seasonal component 234 9.3.4 Forecast of the whole time series 235 9.4 Characterization of time series in natural language 236 9.4.1 Sentences characterizing trend 236 9.4.2 Automatic generation of sentences characterizing trend 238 9.4.3 Mining information from time series 241 References 245 Index 255. |
Record Nr. | UNINA-9910826728003321 |
Novák Vilém <1951->
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Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2016] | ||
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Lo trovi qui: Univ. Federico II | ||
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An introduction to many-valued and fuzzy logic : semantics, algebras, and derivation systems / / Merrie Bergmann [[electronic resource]] |
Autore | Bergmann Merrie |
Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2008 |
Descrizione fisica | 1 online resource (xii, 329 pages) : digital, PDF file(s) |
Disciplina | 511.3/13 |
Soggetto topico |
Fuzzy logic
Many-valued logic |
ISBN |
1-107-18491-6
0-511-80112-2 0-511-64957-6 0-511-37645-6 0-511-57418-5 0-511-37739-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Review of classical propositional logic -- Review of classical first-order logic -- Alternative semantics for truth-values and truth-functions : numeric truth-values and abstract algebras -- Three-valued propositional logics : semantics -- Derivation systems for three-valued propositional logic -- Three-valued first-order logics : semantics -- Derivation systems for three-valued first-order logics -- Alternative semantics for three-valued logic -- The principle of charity reconsidered and a new problem of the fringe -- Fuzzy propositional logics : semantics -- Fuzzy algebras -- Derivation systems for fuzzy propositional logics -- Fuzzy first-order logics : semantics -- Derivation systems for fuzzy first-order logics -- Extensions of fuzziness -- Fuzzy membership functions. |
Altri titoli varianti | An Introduction to Many-Valued & Fuzzy Logic |
Record Nr. | UNINA-9910454419603321 |
Bergmann Merrie
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Cambridge : , : Cambridge University Press, , 2008 | ||
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Lo trovi qui: Univ. Federico II | ||
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An introduction to many-valued and fuzzy logic : semantics, algebras, and derivation systems / / Merrie Bergmann [[electronic resource]] |
Autore | Bergmann Merrie |
Pubbl/distr/stampa | Cambridge : , : Cambridge University Press, , 2008 |
Descrizione fisica | 1 online resource (xii, 329 pages) : digital, PDF file(s) |
Disciplina | 511.3/13 |
Soggetto topico |
Fuzzy logic
Many-valued logic Lògica borrosa Lògica multivalent |
Soggetto genere / forma | Llibres electrònics |
ISBN |
1-107-18491-6
0-511-80112-2 0-511-64957-6 0-511-37645-6 0-511-57418-5 0-511-37739-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Review of classical propositional logic -- Review of classical first-order logic -- Alternative semantics for truth-values and truth-functions : numeric truth-values and abstract algebras -- Three-valued propositional logics : semantics -- Derivation systems for three-valued propositional logic -- Three-valued first-order logics : semantics -- Derivation systems for three-valued first-order logics -- Alternative semantics for three-valued logic -- The principle of charity reconsidered and a new problem of the fringe -- Fuzzy propositional logics : semantics -- Fuzzy algebras -- Derivation systems for fuzzy propositional logics -- Fuzzy first-order logics : semantics -- Derivation systems for fuzzy first-order logics -- Extensions of fuzziness -- Fuzzy membership functions. |
Altri titoli varianti | An Introduction to Many-Valued & Fuzzy Logic |
Record Nr. | UNINA-9910782699303321 |
Bergmann Merrie
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Cambridge : , : Cambridge University Press, , 2008 | ||
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Lo trovi qui: Univ. Federico II | ||
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