Heat Flow Prediction in Songliao Basin Based on Deep Neural Network
Lige Bai,
Jing Li,
Zhaofa Zeng
Abstract:The heat flow is the key data for accurately predicting the contribution of underground heat, but due to the high cost of measurement, the spatial difference is huge, and the heat flow information in some areas is little known. This paper uses deep neural network technology to perform machine learning on a large number of relevant geological and geophysical features and heat flow measurements on a global scale. In addition, the model uncertainty quantification process is introduced, and the reliability of the … Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.