The Ordered Weighted Averaging Operators: Theory and Applications

The Ordered Weighted Averaging Operators: Theory and Applications


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The Ordered Weighted Averaging Operators: Theory and Applications by Ronald R. Yager

This volume is the first in the literature on the increasingly popular Ordered Weighted Averaging (OWA) operators. These OWA operators make it possible to change the form of aggregation from the 'pessimistic' minimum-type aggregation through all intermediate types including the conventional arithmetic mean and nonconventional aggregations, to the 'optimistic' maximum-type aggregations. Included are contributions from a number of fields where these operators have been applied. These fields are decision analysis under uncertainty, learning and classification, multi-person decision-making and consensus formation, and flexible database querying and information retrieval.

Product Details

ISBN-13: 9780792399346
Publisher: Springer US
Publication date: 05/31/1997
Edition description: 1997
Pages: 347
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

Preface. 1: Basic Issues in Aggregation. Kolmogorov's Theorem and its Impact on Soft Computing; H.T. Nguyen, V. Kreinovich. Possibility and Necessity in Weighted Aggregation; C. Carlsson, et al. OWA Operators and an Extension of the Contrast Model; B. Bouchon-Meunier, M. Rifqi. Equivalence of Changes in Proportions at Crossroads of Mathematical Theories; J. Aczél, et al. 2: Fundamental Aspects of OWA Operators. On the Inclusion of Importances in OWA Aggregation; R.R. Yager. On the Linguistic OWA Operator and Extensions; F. Herrera, E. Herrera-Viedma. Alternative Representations of OWA Operators; M. Grabisch. 3: Mathematical Issues and OWA Operators. Useful Tools for Aggregation procedures: Some Consequences and Applications of Strassen's Measurable Hahn-Banach Theorem; H.J. Skala. OWA Specificity; A. Ramer. Ordered Continuous Means and Information; A. Ramer. 4: OWA Operators in Decision Analysis. OWA Operators in Decision Making with Uncertainty and Nonnumeric Payoffs; R.R. Yager, M.T. Lamata. On the Role of Immediate Probability in Various Decision Making Models; K.J. Engemann, R.R. Yager. Risk Management Using Fuzzy Logic and Genetic Algorithms; T.C. Rubinson, G. Geotsi. OWA Operators for Doctoral Student Selection Problem; C. Carlsson, et al. 5: OWA Operators in Multicriteria and Multiperson Decision Making. Beyond Min Aggregation in Multicriteria Decision: (Ordered) Weighted Mean, Discri-Min, Leximin; D. Dubois, et al. OWA Operators in Group Decision Making and Consensus Reaching Under Fuzzy Preferences and Fuzzy Majority; J. Kacprzyk, et al. Applications of the Linguistic OWA Operators in Group Decision Making; F. Herrera, etal. Aggregation Rules in Committee Procedures; J. Montero, V. Cutello. 6: OWA Operators in Querying and Information Retrieval. Quantified Statements and Some Interpretations for the OWA Operators; P. Bosc, L. Liétard. Using OWA Operators in Flexible Query Processing; M.-A. Vila, et al. Application of OWA Operators to Soften Information Retrieval Systems; G. Bordogna, G. Pasi. Implementation of OWA Operators in Fuzzy Querying for Microsoft Access; J. Kacprzyk, S. Zadrozny. 7: OWA Operators in Learning and Classification. OWA-Based Computing: Learning Algorithms; W. Pedrycz. OWA Operators in Machine Learning from Imperfect Examples; J. Kacprzyk. An Application of OWA Operators to the Aggregation of Multiple Classification Decisions; L.I. Kuncheva. Index.

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