@inproceedings{8fc0466333174a8e9e216195becaec94,
title = "Temperature and humidity compensation for MOS gas sensor based on random forests",
abstract = "The outputs of Metal Oxide Semiconductor (MOS) gas sensors drift due to the change of temperature and humidity in the environment. This phenomenon leads to additional errors in the measurement and the test precision and measurement stability of gas sensor are greatly affected. A novel strategy for temperature and humidity compensation for MOS Gas Sensor is proposed in this paper. The environmental gas concentrations are measured separately and accurately based Random Forest (RF) method to demonstrate that the proposed strategy is superior at both accuracy and runtime compared with the conventional methods, such as RBF neural network and BP neural network. Results show that the proposed methodology provides a better solution to temperature and humidity drift. The accuracy of the environmental gas sensor array improves about 1\%.",
keywords = "Random forest, Sensor array, Sensor drift, Temperature and humidity compensation",
author = "Peng Xu and Kai Song and Xiaodong Xia and Yinsheng Chen and Qi Wang and Guo Wei",
note = "Publisher Copyright: {\textcopyright} 2017, Springer Nature Singapore Pte Ltd.; International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017 ; Conference date: 22-09-2017 Through 24-09-2017",
year = "2017",
doi = "10.1007/978-981-10-6373-2\_14",
language = "英语",
isbn = "9789811063725",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "135--145",
editor = "Dong Yue and Tengfei Zhang and Chen Peng and Dajun Du and Min Zheng and Qinglong Han",
booktitle = "Intelligent Computing, Networked Control, and Their Engineering Applications - International Conference on Life System Modeling and Simulation, LSMS 2017 and International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2017, Proceedings",
address = "德国",
}