TY - GEN
T1 - Committee machine with over 95% classification accuracy for combustible gas identification
AU - Minghua, Shi
AU - Bermak, Amine
PY - 2006
Y1 - 2006
N2 - Gas identification represents a big challenge for pattern recognition systems due to several particular problems such as non-selectivity and drift. This paper proposes a gas identification committee machine (CM), which combines various gas identification algorithms, to obtain a unified decision with improved accuracy. The CM combines 5 different classifiers: K Nearest Neighbors (KNN), Multi-layer Perceptron (MLP), Radial Basis Function (RFB), Gaussian Mixture Model (GMM) and Probabilistic PCA (PPCA). A data acquisition system using tin-oxide gas sensor array has been designed in order to create a real gas data set. The committee machine is implemented by assembling the outputs of these gas identification algorithms based on weighted combination rule. Experiments on real sensors' data proved the effectiveness of our system with an improved accuracy 95.9% over the individual classifiers.
AB - Gas identification represents a big challenge for pattern recognition systems due to several particular problems such as non-selectivity and drift. This paper proposes a gas identification committee machine (CM), which combines various gas identification algorithms, to obtain a unified decision with improved accuracy. The CM combines 5 different classifiers: K Nearest Neighbors (KNN), Multi-layer Perceptron (MLP), Radial Basis Function (RFB), Gaussian Mixture Model (GMM) and Probabilistic PCA (PPCA). A data acquisition system using tin-oxide gas sensor array has been designed in order to create a real gas data set. The committee machine is implemented by assembling the outputs of these gas identification algorithms based on weighted combination rule. Experiments on real sensors' data proved the effectiveness of our system with an improved accuracy 95.9% over the individual classifiers.
KW - Committee machine
KW - Gas identification
KW - Pattern recognition
KW - Tin oxide gas sensor
UR - https://www.scopus.com/pages/publications/36849058936
U2 - 10.1109/ICECS.2006.379925
DO - 10.1109/ICECS.2006.379925
M3 - Conference contribution
AN - SCOPUS:36849058936
SN - 1424403952
SN - 9781424403950
T3 - Proceedings of the IEEE International Conference on Electronics, Circuits, and Systems
SP - 862
EP - 865
BT - ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems
T2 - ICECS 2006 - 13th IEEE International Conference on Electronics, Circuits and Systems
Y2 - 10 December 2006 through 13 December 2006
ER -