Predicting the Height of the Hydraulic Fracture Zone Using a Convolutional Neural Network

IF 2.1 4区环境科学与生态学 Q3 WATER RESOURCES

Mine Water and the Environment Pub Date : 2023-08-26 DOI:10.1007/s10230-023-00950-6

Peihe Zhai, Nianzheng Li

引用次数: 0

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利用卷积神经网络预测水力裂缝带高度

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来源期刊

Mine Water and the Environment WATER RESOURCES-

CiteScore

5.00

自引率

14.30%

发文量

审稿时长

3 months

期刊介绍： Mine Water and the Environment welcomes original contributions that address either technical questions or practical issues related to the evaluation, prediction, prevention, or control of water problems at mining operations or their impact on the environment. The journal and its audience is interdisciplinary. Manuscripts should convey new technical information and be of potential interest to researchers and/or practitioners in this field. Laboratory and field experiments, modelling efforts, studies of relevant field sites, technical evaluations of new technology, and engineering applications are all appropriate.