首页|Researchers from Southern University of Science and Technology (SUSTech) Provide Details of New Studies and Findings in the Area of Machine Learning (Selective Discrimination of Vocs Gases At Ppb-level Using Mos Gas Sensor In Temperature-pulsed…)
Researchers from Southern University of Science and Technology (SUSTech) Provide Details of New Studies and Findings in the Area of Machine Learning (Selective Discrimination of Vocs Gases At Ppb-level Using Mos Gas Sensor In Temperature-pulsed…)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Elsevier
Fresh data on Machine Learning are presented in a new report. According to news re- porting originating from Shenzhen, People's Republic of China, by NewsRx correspondents, research stated, “Due to the complicated gas-sensing process on the surface of metal oxide semiconductors (MOS), it is hard to accurately characterize the transient changes of MOS gas sensor. This paper introduces a modified Hill equation to quantitatively analyze the instantaneous resistance of MOS gas sensors operating in temperature-pulsed operation mode, to extract the gas-sensing dynamic features and key parameters for the selective identification of various volatile organic compounds (VOCs) gases (such as ethanol, formaldehyde, toluene and acetone) by machine learning algorithms.”
ShenzhenPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningSouthern University of Science and Technology (SUSTech)
NETL
NSTL
Elsevier
