The DOI matches its Crossref record; 186 of the 186 references it cites were found in a registry or an index.
Deep learning and its application in geochemical mapping
Abstract
Abstract Machine learning algorithms have been applied widely in the fields of natural science, social science and engineering. It can be expected that machine learning approaches especially deep learning algorithms will help geoscientists to discover mineral deposits through processing of various geoscience datasets. This study reviews the state-of-the-art application of deep learning algorithms for processing geochemical exploration data and mining the geochemical patterns. Deep learning algorithms can deal with complex and nonlinear problems and, therefore, can enhance the identification of geochemical anomalies and the recognition of hidden patterns. Applied geochemistry needs more applications of machine learning and/or deep learning algorithms.
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Cited by
Deep learning controller for nonlinear system based on Lyapunov stability criterion
Zaki, A. M., El-Nagar, A. M., El-Bardini, M., & Soliman, F. A. S. (2021) · Neural Computing and Applications · doi:10.1007/s00521-020-05077-1 · Cited by 29
Metadata
- Authors
- Zuo, R., Xiong, Y., Wang, J., & Carranza, E. J. M.
- Venue
- Earth-Science Reviews
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 192
- Pages
- 1-14
- ISSN
- 0012-8252 (ISSN-L)
- OpenAlex
- W2920641855
- Cited by
- 426
- References
- 186
- FWCI
- 17.61
- Type
- journal article
- Language
- en
- Open access
- closed
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