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Deep learning and its application in geochemical mapping
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DOI：10.1016/j.earscirev.2019.02.023.png)
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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.
Keyword:
Applied geochemistry
Geochemical mapping
Geochemical patterns
Machine learning
Deep learning
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Singularity analysis based on wavelet transform of fractal measures for identifying geochemical anomaly in mineral exploration基于分形测度小波变换的奇异性分析在矿产勘查地球化学异常识别中的应用
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