Title :
Neuro-fuzzy TSK network for calibration of semiconductor sensor array for gas measurements
Author :
Osowski, Stanislaw ; Linh, Tran Hoai ; Brudzewski, Kazimierz
Author_Institution :
Warsaw Univ. of Technol., Poland
fDate :
6/1/2004 12:00:00 AM
Abstract :
The neuro-fuzzy network applying Takagi-Sugeno-Kang (TSK) fuzzy reasoning for the calibration of the semiconductor sensor array is developed in this paper. The structure, as well as the learning algorithm of the neuro-fuzzy network, is presented and tested on the example of estimation of the concentration of gas components in the gaseous mixture (so-called artificial nose problem). The results of numerical experiments are presented and discussed.
Keywords :
calibration; fuzzy neural nets; gas sensors; learning systems; Takagi-Sugeno-Kang fuzzy reasoning; calibration; gas components; gas measurements; gaseous mixture; learning algorithm; neuro-fuzzy network; semiconductor sensor array; Calibration; Fuzzy neural networks; Fuzzy reasoning; Fuzzy systems; Gas detectors; Input variables; Nose; Pollution measurement; Sensor arrays; Testing; Gas measurement; TSK; network; neuro-fuzzy Takagi–Sugeno–Kang; semiconductor sensor calibration;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2004.827318
