Intelligent classification using adaptive fuzzy logic systems

Author

Kodogiannis, Vassilis S. ; Petrounias, Ilias ; Lygouras, John N.

Author_Institution

Centre for Syst. Anal., Univ. of Westminster, London

Volume

1

fYear

2008

fDate

6-8 Sept. 2008

Firstpage

42621

Lastpage

42626

Abstract

Fuzzy systems are currently finding practical applications, ranging from ldquosoftrdquo regulatory control in consumer products to accurate modeling of non-linear systems. A novel approach, based on adaptive fuzzy logic systems, has been discussed in this paper. Its performance is evaluated through a simulation study, using metered data collected from a roadside microphone-array sensor at the Valle dpsilaAosta highway in north-western Italy. The results indicate that the fuzzy classifier based on the proposed defuzzification method, namely area of balance (AOB), provide more accurate classifications compared to other classifiers.

Keywords

acoustic signal detection; acoustic signal processing; adaptive control; feature extraction; fuzzy control; fuzzy set theory; microphone arrays; multilayer perceptrons; neurocontrollers; nonlinear control systems; road vehicles; signal classification; acoustic signature signal; adaptive fuzzy logic system; area of balance; defuzzification method; features extraction; fuzzy set theory; intelligent fuzzy classification; multi layer perceptron; nonlinear system; soft regulatory control; vehicles detection; Adaptive control; Adaptive systems; Consumer products; Fuzzy logic; Fuzzy sets; Fuzzy systems; Intelligent systems; Nonlinear control systems; Programmable control; Shape; Fuzzy systems; Neural Networks; Vehicle Classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems, 2008. IS '08. 4th International IEEE Conference

Conference_Location

Varna

Print_ISBN

978-1-4244-1739-1

Electronic_ISBN

978-1-4244-1740-7

Type

conf

DOI

10.1109/IS.2008.4670453

Filename

4670453