Fuzzy Set Theory: Applications in the Social Sciences
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Fuzzy Set Theory: Applications in the Social Sciences

by Michael Smithson, Jay Verkuilen
     
 

ISBN-10: 076192986X

ISBN-13: 9780761929864

Pub. Date: 02/28/2006

Publisher: SAGE Publications

Fuzzy set theory deals with sets or categories whose boundaries are blurry or, in other words, "fuzzy." This book presents an accessible introduction to fuzzy set theory, focusing on its applicability to the social sciences. Unlike most books on this topic, Fuzzy Set Theory: Applications in the Social Sciences provides a systematic, yet practical guide for

Overview

Fuzzy set theory deals with sets or categories whose boundaries are blurry or, in other words, "fuzzy." This book presents an accessible introduction to fuzzy set theory, focusing on its applicability to the social sciences. Unlike most books on this topic, Fuzzy Set Theory: Applications in the Social Sciences provides a systematic, yet practical guide for researchers wishing to combine fuzzy set theory with standard statistical techniques and model-testing.

Product Details

ISBN-13:
9780761929864
Publisher:
SAGE Publications
Publication date:
02/28/2006
Series:
Quantitative Applications in the Social Sciences Series, #147
Edition description:
New Edition
Pages:
112
Product dimensions:
5.50(w) x 8.50(h) x (d)

Table of Contents

Series Editor’s Introduction
Acknowledgments
1. Introduction
2. An Overview of Fuzzy Set Mathematics
2.1 Set Theory
2.2 Why Fuzzy Sets?
2.3 The Membership Function
2.4 Operations of Fuzzy Set Theory
2.5 Fuzzy Numbers and Fuzzy Variables
2.6 Graphical Representations of Fuzzy Sets
3. Measuring Membership
3.1 Introduction
3.2 Methods for Constructing Membership Functions
3.3 Measurement Properties Required for Fuzzy Sets
3.4 Measurement Properties of Membership Functions
3.5 Uncertainty Estimates in Membership Assignment
4. Internal Structure and Properties of a Fuzzy Set
4.1 Cardinality: The Size of a Fuzzy Set
4.2 Probability Distributions for Fuzzy Sets
4.3 Defining and Measuring Fuzziness
5. Simple Relations Between Fuzzy Sets
5.1 Intersection, Union, and Inclusion
5.2 Detecting and Evaluating Fuzzy Inclusion
5.3 Quantifying and Modeling Inclusion: Ordinal Membership Scales
5.4 Quantified and Comparable Membership Scales
6. Multivariate Fuzzy Set Relations
6.1 Compound Set Indexes
6.2 Multiset Relations: Comorbidity, Covariation, and Co-Occurrence
6.3 Multiple and Partial Intersection and Inclusion
7. Concluding Remarks
References
Index
About the Authors

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