On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
k-order additive discrete fuzzy measures and their representation
Fuzzy Sets and Systems - Special issue on fuzzy measures and integrals
Handbook of Granular Computing
Handbook of Granular Computing
Aggregation Functions: A Guide for Practitioners
Aggregation Functions: A Guide for Practitioners
Nonlinear Integrals And Their Applications In Data Mining
Nonlinear Integrals And Their Applications In Data Mining
A measure based approach to the fusion of possibilistic and probabilistic uncertainty
Fuzzy Optimization and Decision Making
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We discuss the use of monotonic set measures for the representation of uncertain information. We look at some important examples of measure-based uncertainty, specifically probability and possibility and necessity. Others types of uncertainty such as cardinality based and quasi-additive measures are discussed. We consider the problem of determining the representative value of a variable whose uncertain value is formalized using a monotonic set measure. We note the central role that averaging and particularly weighted averaging operations play in obtaining these representative values. We investigate the use of various integrals such as the Choquet and Sugeno for obtaining these required averages. We suggest ways of extending a measure defined on a set to the case of fuzzy sets and the power sets of the original set. We briefly consider the problem of question answering under uncertain knowledge.