AbstractThe gas sensor data set collected by Vergara et al. was processed, select two different feature extraction methods:the hand-designed feature method and the principal component analysis method,and then combined with the Z-score data normalization method to form two feature engineering schemes for experiments. The processed data of the two schemes were fed into the artificial neural network model for training and testing. The prediction results show that the model with the principal component analysis method with Z-score normalization is more accurate. The prediction rate of the model can be improved by choosing different feature extraction methods to process the data with the same neural network structure.
ZOU Yanan,SHI Xueying,WU Qingyun. Analytical Methods for Processing Gas Sensor Data Sets[J]. Journal of Jilin Institute of Chemical Technology,
2022, 39(11): 1-5.
