학술논문

Sugeno fuzzy integral generalizations for Sub-normal Fuzzy set-valued inputs
Document Type
Conference
Source
2012 IEEE International Conference on Fuzzy Systems Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on. :1-8 Jun, 2012
Subject
Computing and Processing
Components, Circuits, Devices and Systems
Frequency selective surfaces
Frequency modulation
Aging
Estimation
Radar
Educational institutions
Electronic mail
Sugeno fuzzy integral
SuFI
NDFI
fuzzy set valued integrands
extension principle
Language
ISSN
1098-7584
Abstract
In prior work, Grabisch put forth a direct (i.e., result of the Extension Principle) generalization of the Sugeno fuzzy integral (FI) for fuzzy set (FS)-valued normal (height equal to one) integrands and number-based fuzzy measures (FMs). Grabisch's proof is based in large on Dubois and Prade's analysis of functions on intervals, fuzzy numbers (thus normal FSs) and fuzzy arithmetic. However, a case not studied is the extension of the FI for sub-normal FS integrands. In prior work, we described a real-world forensic application in anthropology that requires fusion and has sub-normal FS inputs. We put forth an alternative non-direct approach for calculating FS results from sub-normal FS inputs based on the use of the number-valued integrand and number-valued FM Sugeno FI. In this article, we discuss a direct generalization of the Sugeno FI for sub-normal FS integrands and numeric FMs, called the Sub-normal Fuzzy Integral (SuFI). To no great surprise, it turns out that the SuFI algorithm is a special case of Grabisch's generalization. An algorithm for calculating SuFI and its mathematical properties are compared to our prior method, the Non-Direct Fuzzy Integral (NDFI). It turns out that SuFI and NDFI fuse in very different ways. We assert that in some settings, e.g., skeletal age-at-death estimation, NDFI is preferred to SuFI. Numeric examples are provided to stress important inner workings and differences between the FI generalizations.