Title | The Ordered Weighted Averaging Operators [electronic resource] : Theory and Applications / edited by Ronald R. Yager, Janusz Kacprzyk |
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Imprint | Boston, MA : Springer US : Imprint: Springer, 1997 |
Connect to | http://dx.doi.org/10.1007/978-1-4615-6123-1 |
Descript | X, 347 p. online resource |
1. Basic Issues in Aggregation -- Kolmogorovโ s theorem and its impact on soft computing -- Possibility and necessity in weighted aggregation -- OWA operators and an extension of the contrast model -- Equivalence of changes in proportions at crossroads of mathematical theories -- 2. Fundamental Aspects of OWA Operators -- On the inclusion of importances in OWA aggregation -- On the linguistic OWA operator and extensions -- Alternative representations of OWA operators -- 3. Mathematical Issues and OWA Operators -- Useful tools for aggregation procedures: some consequences and applications of Strossen โs measurable Hahn-Banach theorem -- OWA specificity -- Ordered continuous means and information -- 4. OWA Operators in Decision Analysis -- OWA operators in decision making with uncertainty and nonnumeric payoffs -- On the role of immediate probability in various decision making models -- Risk management using fuzzy logic and genetic algorithms -- OWA operators for doctoral student selection problem -- 5. OWA Operators in Multicriteria and Multiperson Decision Making -- Beyond min aggregation in multicriteria decision: (ordered) weighted mean, discri-min, leximin -- OWA operators in group decision making and consensus reaching under fuzzy preferences and fuzzy majority -- Applications of the linguistic OWA operators in group decision making -- Aggregation rules in committee procedures -- 6. OWA Operators in Querying and Information Retrieval -- Quantified statements and some interpretations for the OWA operators -- Using OWA operators in flexible query processing -- Application of OWA operatrors to soften information retrieval systems -- Implementation of OWA operators in fuzzy querying for Microsoft Access -- 7. OWA Operators in Learning and Classification -- OWA-based computing: learning algorithms -- OWA operators in machine learning from imperfect examples -- An application of OWA operators to the aggregation of multiple classification decisions