Title
Determining nonnegative monotone set functions based on Sugeno's integral: an application of genetic algorithms
Abstract
Regarding the set of all information sources as the universe of discourse, we used a nonnegative monotone set function defined on its power set to describe the importance of each individual information source and their varied combinations. Such a set function is called an importance measure or a fuzzy measure. The Sugeno integral with respect to the nonnegative monotone set function possesses many desired properties, such as the fuzzy linearity when the set function is fuzzy additive, and can be adopted as an aggregation means in information fusion. In real problems, viewing the Sugeno integral as a multi-input single-output system, we use a genetic algorithm to determine the values of the importance measure from the input-output data of the system. (C) 2000 Elsevier Science B.V. All rights reserved.
Year
DOI
Venue
2000
10.1016/S0165-0114(98)00304-2
Fuzzy Sets and Systems
Keywords
Field
DocType
information fusion,data processing,nonadditive set functions,nonlinear integrals,optimization,least-square method,genetic algorithms
Set function,Discrete mathematics,Mathematical optimization,Sugeno integral,Fuzzy logic,Fuzzy measure theory,Fuzzy control system,Power set,Lebesgue integration,Monotone polygon,Mathematics
Journal
Volume
Issue
ISSN
112
1
0165-0114
Citations 
PageRank 
References 
10
1.71
6
Authors
3
Name
Order
Citations
PageRank
Zhenyuan Wang168490.22
Kwong-Sak Leung21887205.58
Jia Wang3101.71