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- W2377062022 abstract "Recognition of ethanol, acetone, benzene, toluene and xylene was performed by using 6 doped nano ZnO gas sensors. It was proved that sensitivities and selectivity of gas sensors could be reasonably improved by dopants. K-nearest neighbour (k-NN), linear discriminant analysis (LDA), back-propagation artificial neural network (BP-ANN), probabilistic neural network (PNN) and learning vector quantization (LVQ) were compared for their suitability on classifying volatile organic compounds (VOCs). The accuracy of BP-ANN in terms of predicting tested samples was 100% and the highest among the pattern recognition algorithms. This work shows the potential application of the gas sensor arrays for monitoring the air quality." @default.
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- W2377062022 date "2006-01-01" @default.
- W2377062022 modified "2023-09-25" @default.
- W2377062022 title "Recognition of Ethanol, Acetone, Benzene, Toluene and Xylene Using Nano ZnO Gas Sensor Array" @default.
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