A New Approach for Calculating Implications of Fuzzy Rules

Authors:
Tuan D. Pham
Affiliations:
-
Venue:
ICAIS '02 Proceedings of the 2002 IEEE International Conference on Artificial Intelligence Systems (ICAIS'02)
Year:
2002

Citing 0
Cited 2

A simple and effective detection technique of 2D electrophoresis image protein spots

ISCGAV'05 Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
Objective data reduction algorithm of proteomic mass spectrum

ISCGAV'05 Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

Fuzzy inference systems have been pervasive in many areas of applications concerning machine learning and decision analysis where numerical computation and human heuristics integrate. This paper introduces an approach for computing the implications of fuzzy rules that consist of multiple input variables. Input variables are partitioned on the basis of information gain, and multiple secondary input attributes are computed by the Choquet fuzzy integral. Theproposed model is computationally efficient in both capturing and aggregating attributes at detailed levels.