DocumentCode :
477744
Title :
The Sugeno Integral and Its Applications of Nonadditive Set Functions Based on Sigma-Lambda  Rules
Author :
Chen, Li ; Gong, Zengtai ; Duan, Gang
Author_Institution :
Dept. of Math., Lanzhou City Univ., Lanzhou
Volume :
1
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
650
Lastpage :
654
Abstract :
Sugeno integral is used as an aggregation tool in information fusion which could be regarded as the inverse problem of information fusion as well as in nonlinear multi-regressions and nonlinear classification. Introducing more types of nonlinear integrals with provide more choices for various of objectives and components in these problems. However, when sample space is huge, regarding needs the information contribution to obtain is very difficult, this paper has carried on the discussion on this. In this paper, first we introduce a kind of nonadditive measure based on sigma-lambda rules and its calculate of the defect of additivity are given. Then based on this, we could calculate contributions of their joint attributes by means of sigma-lambda rules based on the contributions of individual attributes. Finally, the lower integral and upper Sugeno integral of the nonadditive set functions based on sigma-lambda rules are defined and calculated by the integer program problems.
Keywords :
integer programming; integral equations; inverse problems; nonlinear equations; pattern classification; regression analysis; set theory; Sugeno integral; aggregation tool; information fusion; integer program problems; inverse problem; nonadditive set functions; nonlinear classification; nonlinear integrals; nonlinear multiregressions; sigma-lambda rules; Databases; Educational institutions; Fuzzy systems; Information science; Inverse problems; Mathematical model; Mathematics; Transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Shandong
Print_ISBN :
978-0-7695-3305-6
Type :
conf
DOI :
10.1109/FSKD.2008.668
Filename :
4666056
Link To Document :
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