A Gas Sensor Array Model Calibration Method Based on Conditional Generative Adversarial Network for Data Augmentation
A gas sensor and condition generation technology, applied in biological neural network models, standard gas analyzers, calculation models, etc., can solve the problems of sensor model calibration difficulties, model calibration accuracy decline, and difficult acquisition, etc., to expand the concentration range and reduce Cost, effect of increasing diversity
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[0046] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.
[0047] like figure 1 As shown, the present invention provides a gas sensor array model calibration method for data augmentation based on conditional generative confrontation network, and the specific implementation process is as follows:
[0048] 1. Experimental data description
[0049] This embodiment uses the temperature modulation gas sensor data set (Gas sensor array temperature modulation Data Set) measured by Javier Burgués and Santiago Marco. The dataset is measured by 14 temperature-modulated metal oxide (MOX) gas sensors. Its chemical detection platform was exposed to a mixture of carbon monoxide and humid synthetic gas in a gas chamber. These sensors produced time-varying multivariate responses to different gas stimuli. The entire measurement process lasted 3 wee...
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