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A novel detection method based on ZnO metal-oxide sensors, capable of detecting various species and concentrations of aimed volatile organic compounds (VOCs), has been proposed in this article. In conjunction with signal processing algorithms, the characteristic signals of the sensors operated under temperature modulating are investigated. When the sensor is operating in the temperature modulation mode and is exposed to different detection gases, it will display different output waveforms. Considering the stability of the sensors in practical applications, general regression neural network (GRNN) is used to distinguish the species and concentration of gas in detail.
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Yuan et al. (2019) studied this question.
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