| 刘晓梅,李新虎,马天录,赵元元.深度学习及其在地质领域中的应用[J].矿产勘查,2024,15(2):281-291 |
| 深度学习及其在地质领域中的应用 |
| Deep learning and its application in geology |
| 投稿时间：2022-11-18 修订日期：2023-07-19 |
| DOI：10.20008/j.kckc.202402011 |
| 中文关键词: 深度学习 神经网络 监督学习 无监督学习 地质领域 |
| 英文关键词: deep learning neural networks supervised learning unsupervised learning geology |
| 基金项目:本文受国家自然科学基金（41502137）资助。 |
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| 摘要点击次数: 2142 |
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| 中文摘要: |
| 深度学习技术的快速发展将成为地质领域再出发的助推剂，深度学习是人工智能范畴内的一个重要分支，是一种以人工神经网络为基本框架，从大量历史数据中学习规律并预测新数据的算法。为了充分理解深度学习在地质领域的应用价值，明确其在地质领域应用中存在的挑战和机遇，本文在系统阐述深度学习的发展过程、方法分类以及常见的4种深度学习模型的基础上，对比了它们在地质领域应用的特点和优势。主要从基础地质、地质勘探、地质灾害以及水文地质4个方面介绍了深度学习在地质领域应用的研究和进展，最后根据现有的情况给出了未来发展的建议，为深度学习在地质领域中应用可能遇到的机遇和挑战提供参考。 |
| 英文摘要: |
| The rapid development of deep learning technology will become a booster for the re-start of the geological field. Deep learning is an important branch in the field of artificial intelligence. It is an algorithm that takes artificial neural network as the basic framework to learn rules from a large number of historical data and predict new data. In order to fully understand the application value of deep learning in the field of geology， and clarify the challenges and opportunities of its application in the field of geology. On the basis of systematically describing the development process， method classification and four common deep learning models， this paper compares the characteristics and advantages of their application in the geological field， introduces the research progress of the application of deep learning in basic geology， geological exploration， geological hazards， hydrogeology， and gives suggestions for future development according to the existing situation， It provides reference for the opportunities and challenges that may be encountered in the application of deep learning in the geological field. |
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