Fuzzy Logic An Introductory Course for Engineering Students
This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introd...
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| Format: | E-Book Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham
Springer Nature
2015
Springer Springer International Publishing AG Springer International Publishing |
| Ausgabe: | 1 |
| Schriftenreihe: | Studies in Fuzziness and Soft Computing |
| Schlagworte: | |
| ISBN: | 3319142038, 9783319142036, 331914202X, 9783319142029 |
| ISSN: | 1434-9922, 1860-0808 |
| Online-Zugang: | Volltext |
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| Abstract | This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications. |
|---|---|
| AbstractList | This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical models. Moreover, it makes them familiar with fuzzy control, an important topic in the engineering field. The book offers an unconventional introductory textbook on fuzzy logic, presenting theory together with examples and not always following the typical mathematical style of theorem-corollaries. Primarily intended to support engineers during their university studies, and to spark their curiosity about fuzzy logic and its applications, the book is also suitable for self-study, providing a valuable resource for engineers and professionals who deal with imprecision and non-random uncertainty in real-world applications. |
| Author | Eciolaza, Luka Trillas, Enric |
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| BackLink | https://cir.nii.ac.jp/crid/1130000795062612352$$DView record in CiNii |
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| Copyright | Springer International Publishing Switzerland 2015 |
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| DOI | 10.1007/978-3-319-14203-6 |
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| Discipline | Engineering Computer Science Mathematics |
| EISBN | 3319142038 9783319142036 |
| EISSN | 1860-0808 |
| Edition | 1 2015 |
| Editor | Eciolaza, Luka |
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| ISBN | 3319142038 9783319142036 331914202X 9783319142029 |
| ISSN | 1434-9922 |
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| Notes | Includes bibliographical references (p. 203-204) |
| OCLC | 902624740 |
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| PageCount | 211 |
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| PublicationSeriesTitle | Studies in Fuzziness and Soft Computing |
| PublicationSeriesTitleAlternate | Studies in Fuzziness |
| PublicationYear | 2015 |
| Publisher | Springer Nature Springer Springer International Publishing AG Springer International Publishing |
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| RelatedPersons | Kacprzyk, Janusz |
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| Snippet | This book introduces readers to fundamental concepts in fuzzy logic. It describes the necessary theoretical background and a number of basic mathematical... |
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| SubjectTerms | Computational Intelligence Control and Systems Theory Engineering Engineering & allied operations Fuzzy logic Symbolic and Algebraic Manipulation |
| Subtitle | An Introductory Course for Engineering Students |
| TableOfContents | 4.3 Which Relevant Properties Do Have a Fuzzy Binary Relation? -- 4.4 The Concept of T-State -- 4.5 Fuzzy relations and α-cuts -- 5 T-Preorders and T-Indistinguishabilities -- 5.1 Which Is the Aim of This Section? -- 5.2 The Characterization of T-Preorders -- 5.3 The Characterization of T-Indistinguishabilities -- 6 Fuzzy Arithmetic -- 6.1 Introduction -- 6.2 Fuzzy Numbers -- 6.2.1 Operations with Fuzzy Numbers -- 6.2.2 Operations with Triangular Fuzzy Numbers -- 6.2.3 Note -- 6.3 A Note on the Lattice of Fuzzy Numbers -- 6.3.1 Example -- 6.4 A Note on Fuzzy Quantifiers -- 6.4.1 Quantified Fuzzy Statements -- 7 Fuzzy Measures -- 7.1 Introduction -- 7.2 The Concept of a Measure -- 7.3 Types of Measures -- 7.4 λ-Measures -- 7.5 Measures of Possibility and Necessity -- 7.6 Examples -- 7.7 Probability, Possibility and Necessity -- 7.8 Probability of Fuzzy Sets -- 8 An Introduction to Fuzzy Control -- 8.1 Introduction -- 8.1.1 Note -- 8.2 Revising Conditional and Implications in Fuzzy Control -- 8.2.1 Inference from Imprecise Rules -- 8.2.2 Takagi-Sugeno of Order 1 -- 8.3 Control of Nonlinear Systems -- 8.3.1 State-Space Representation -- 8.3.2 Takagi-Sugeno Models for Control of Nonlinear Systems -- 8.3.3 Stability Analysis -- 8.3.4 Parallel Distributed Compensation -- 8.3.5 Piecewise Bilinear Model -- 8.3.6 Vertex Placement Principle -- Bibliography Intro -- Preface -- Contents -- 1 On the Roots of Fuzzy Sets -- 1.1 A Genesis of Fuzzy Sets -- 1.1.1 L-Degree -- 1.1.2 Fuzzy Sets -- 1.2 Opposite, Negate, and Middle -- 1.2.1 Antonyms -- 1.2.2 Negations -- 1.2.3 Antonyms and Negations -- 1.2.4 Medium Term -- 1.3 AND/OR -- 1.3.1 AND -- 1.3.2 OR -- 1.4 Qualified, Modified, and Constrained Predicates -- 1.4.1 Qualified Predicates -- 1.4.2 Linguistic Modifiers -- 1.4.3 Constrained Predicates -- 1.4.4 Group Meaning -- 1.4.5 Synonims -- 1.5 Linguistic Variables -- 1.5.1 Fuzzy Partition -- 1.6 A Note on Lattices -- 1.6.1 Examples -- 2 Algebras of Fuzzy Sets -- 2.1 Introduction -- 2.1.1 Cartesian Product -- 2.1.2 Extension Principle -- 2.1.3 Preservation of the Classical Case -- 2.1.4 Resolution -- 2.2 The Concept of an `Algebra of Fuzzy Sets' -- 2.2.1 Introduction -- 2.2.2 Algebras of Fuzzy Sets -- 2.2.3 Non-contradiction and Excluded-Middle -- 2.2.4 Decomposable Algebras -- 2.2.5 Standard Algebras of Fuzzy Sets -- 2.2.6 Strong Negations -- 2.2.7 Continuous T-Norms and T-Conorms -- 2.2.8 Laws of Fuzzy Sets -- 2.2.9 Examples -- 2.3 On Aggregating Imprecise Information -- 2.3.1 Aggregation Functions -- 2.3.2 Ordered Weighted Means -- 2.3.3 More on Aggregations -- 2.3.4 Examples -- 3 Reasoning and Fuzzy Logic -- 3.1 What Does It Mean ``Logic''? -- 3.1.1 Logic and Consequence Operators -- 3.1.2 Conjecturing -- 3.2 Reasoning with Conditionals: Representation -- 3.2.1 What is a Conditional? -- 3.2.2 The Case of Boolean Algebras -- 3.2.3 Fuzzy Conditionals -- 3.3 Short Note on Other Modes of Reasoning -- 3.4 Inference with Fuzzy Rules -- 3.4.1 Finite Case -- 3.4.2 Inference with Several Rules -- 3.4.3 Examples -- 3.5 Deffuzification -- 3.6 Rules and Conjectures -- 3.7 Two Final Examples -- 4 Fuzzy Relations -- 4.1 What Is a Fuzzy Relation? -- 4.2 How to Compose Fuzzy Relations? |
| Title | Fuzzy Logic |
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