Improving the Robustness of Prediction Model by Transfer Learning for Interference Suppression of Electronic Nose

This paper gives a solution to solve the interference problem of electronic nose (e-nose), which is ill-posed due to the uncertainty and unpredictability of its instable behavior. Traditional methods for interference suppression are component correction frameworks, which are laborious or little efficient. With interference (especially background interference and sensor drift), the distribution of ...