Possibility theory for the design of information fusion systems. (©2019)
- Record Type:
- Book
- Title:
- Possibility theory for the design of information fusion systems. (©2019)
- Main Title:
- Possibility theory for the design of information fusion systems
- Further Information:
- Note: Basel Solaiman, Éloi Bossé.
- Other Names:
- Solaiman, Basel
Bossé, Éloi, 1956- - Contents:
- Intro -- Preface -- Contents -- Chapter 1: Introduction to Possibility Theory -- 1.1 Introduction -- 1.2 Information Concept -- 1.2.1 Information Element Definition -- 1.2.2 Intrinsic Information Imperfection Types -- 1.3 Possibilistic Information Concept -- References -- Chapter 2: Fundamental Possibilistic Concepts -- 2.1 Introduction -- 2.2 Possibility Distributions Concept -- 2.2.1 Defining a Possibility Distribution -- 2.2.2 Possibility Distribution Models -- 2.2.3 Possibility Distributions Discounting -- 2.2.4 Possibilistic Extension Principle 2.2.5 Specificity Concept and Minimal Specificity Principle (MSP) -- 2.3 Possibility and Necessity Measures -- 2.3.1 Possibility Measure -- 2.3.2 Necessity Measure -- 2.3.3 Duality Relevant Properties of Possibility and Necessity Measures -- 2.3.4 Relative Possibility and Necessity Measures of Ambiguous Events -- 2.3.5 Important Properties of Possibility/Necessity Degrees of Matching -- 2.4 Subnormal Possibility Distributions -- 2.4.1 Possibility Distributions Normalization Methods -- 2.4.1.1 Ordinal Normalization -- 2.4.1.2 Numerical (or Ratio) Normalization 2.4.1.3 Inconsistency Shifting Normalization -- 2.4.2 Duboisś Alternative Necessity Measure -- 2.4.3 Normal Versus Subnormal Distributions Properties -- References -- Chapter 3: Joint Possibility Distributions and Conditioning -- 3.1 Introduction -- 3.2 Joint and Marginal Possibility Distributions -- 3.3 Cylindrical Extension of Non-interactive Possibilistic Variables --Intro -- Preface -- Contents -- Chapter 1: Introduction to Possibility Theory -- 1.1 Introduction -- 1.2 Information Concept -- 1.2.1 Information Element Definition -- 1.2.2 Intrinsic Information Imperfection Types -- 1.3 Possibilistic Information Concept -- References -- Chapter 2: Fundamental Possibilistic Concepts -- 2.1 Introduction -- 2.2 Possibility Distributions Concept -- 2.2.1 Defining a Possibility Distribution -- 2.2.2 Possibility Distribution Models -- 2.2.3 Possibility Distributions Discounting -- 2.2.4 Possibilistic Extension Principle 2.2.5 Specificity Concept and Minimal Specificity Principle (MSP) -- 2.3 Possibility and Necessity Measures -- 2.3.1 Possibility Measure -- 2.3.2 Necessity Measure -- 2.3.3 Duality Relevant Properties of Possibility and Necessity Measures -- 2.3.4 Relative Possibility and Necessity Measures of Ambiguous Events -- 2.3.5 Important Properties of Possibility/Necessity Degrees of Matching -- 2.4 Subnormal Possibility Distributions -- 2.4.1 Possibility Distributions Normalization Methods -- 2.4.1.1 Ordinal Normalization -- 2.4.1.2 Numerical (or Ratio) Normalization 2.4.1.3 Inconsistency Shifting Normalization -- 2.4.2 Duboisś Alternative Necessity Measure -- 2.4.3 Normal Versus Subnormal Distributions Properties -- References -- Chapter 3: Joint Possibility Distributions and Conditioning -- 3.1 Introduction -- 3.2 Joint and Marginal Possibility Distributions -- 3.3 Cylindrical Extension of Non-interactive Possibilistic Variables -- 3.3.1 Projections of a Cylindrical Extension -- 3.3.2 Joint Possibility and Necessity Measures -- 3.4 Conditioning Under the Knowledge of the Joint Possibility Distribution -- 3.4.1 Zadehś Conditioning Rule 3.4.2 Hisdalś Conditioning Rule -- 3.4.3 Dempsterś Conditioning Rule -- 3.4.4 Nguyenś Conditioning Rule -- 3.4.5 Causal Link Conditioning -- 3.5 Conditioning and Belief Revision -- 3.5.1 Crisp Event-Based Possibilistic Revision -- 3.5.2 Unreliable Crisp Event-Based Possibilistic Revision -- 3.5.2.1 Unreliability as a Constraint -- 3.5.2.2 Unreliability as a Certainty Degree -- 3.6 Conditioning and Possibilistic Medical Diagnosis -- References -- Chapter 4: Possibilistic Similarity Measures -- 4.1 Introduction -- 4.2 Taxonomy of Similarity Measures -- 4.2.1 Metric-Based Similarity Measures 4.2.1.1 Metric Distance Measures -- Minkowski Distance -- Canberra Distance -- Hausdorff Distance -- 4.2.1.2 Metric Similarity Measures -- 4.2.2 Set-Based Similarity Measures -- 4.3 Fuzzy Sets Theory and Similarity Measures -- 4.3.1 Metric-Based Similarity Measures of Fuzzy Sets -- 4.3.2 Set-Based Similarity Measures of Fuzzy Sets -- 4.3.3 Implication-Based Similarity Measures of Fuzzy Sets -- 4.4 Possibility Distributions Similarity Measures -- 4.4.1 Definition, Possibilistic Similarity Measures -- 4.4.2 Metric-Based Possibilistic Similarity Measures … (more)
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2019
- Copyright Date:
- 2019
- Extent:
- 1 online resource (294 pages)
- Subjects:
- 511.3/223
Fuzzy sets
Uncertainty (Information theory)
Fuzzy sets
Uncertainty (Information theory)
Electronic books - Languages:
- English
- ISBNs:
- 9783030328535
3030328538
9783030328528
9783030328542
3030328546
9783030328559
3030328554 - Related ISBNs:
- 9783030328528
303032852X - Notes:
- Note: Includes bibliographical references.
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- British Library HMNTS - ELD.DS.480075
- Ingest File:
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