Yager R.R., Kacprzyk J. (eds.) The Ordered Weighted Averaging Operators: Theory and Applications

New York: Springer, 1997. — 342 p.Aggregation plays a central role in many of the technical tasks we are faced with. The importance of this process will become even greater as we move more and more toward becoming an information-centered society, which is happening with the rapid growth of the Internet and the World Wireless Weh. Here we shall be faced with many issues related to the fusion of information. One very pressing issue here is the development of mechanisms to help search for information, a problem that has a strong aggregation-related component. More generally, to model the sophisticated ways in which human beings process information, as well as go beyond human capa­ abilities, we need to provide a basket of aggregation tools. The centrality of aggregation in human thought can be very clearly seen by looking at neural networks, a technology motivated by modeling the human brain. One can see that the basic operations involved in these networks are learning and aggregation. The Ordered Weighted Averaging (OWA) operators provide a parameter­ized family of aggregation operators which include many of the well-known operators such as the maximum, minimum, and simple average.Kolmogorov’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.On the Inclusion of Importances in OWA Aggregations.
On the Linguistic OWA Operator and Extensions.
Alternative Representations of OWA Operators.Useful Tools for Aggregation Procedures: Some Consequences and Applications of Strassen’s Measurable Hahn-Banach-Theorem.
OWA Specificity.
Ordered Continuous Means and Information.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 the doctoral student selection problem.Beyond Min Aggregation in Multicriteria Decision: (Ordered) Weighted Min, 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.Quantified Statements and Some Interpretations for the OWA Operator.
Using OWA Operator in Flexible Query Processing.Application of OWA Operators to Soften Information Retrieval Systems.
Implementation of OWA Operators in Fuzzy Querying for Microsoft Access.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.