Data Mining
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-85040-1_77
Reference10 articles.
1. Agarwal A, Wen T, Chen A, Zhang AY, Niu X, Zhan X, Xue L, Brantley SL (2020) Assessing contamination of stream networks near shale gas development using a new geospatial tool. Environ Sci Technol. https://doi.org/10.1021/acs.est.9b06761
2. Barbier S, Huang F, Andreani M, Tao R, Hao J, Eleish A, Prabhu A, Minhas O, Fontaine K, Fox P, Daniel I (2020) A review of H2, CH4, and hydrocarbon formation in experimental serpentinization using network analysis. Front Earth Sci 8:209. https://doi.org/10.3389/feart.2020.00209
3. Cracknell MJ, Reading AM, McNeill AW (2014) Mapping geology and volcanic-hosted massive sulfide alteration in the Hellyer-Mt Charter region, Tasmania, using Random Forests™ and Self-organising Maps. Aust J Earth Sci 61:287–304. https://doi.org/10.1080/08120099.2014.858081
4. Han J, Pei J, Kamber M (2011) Data mining: concepts and techniques, the Morgan Kaufmann series in data management systems. Elsevier Science, Saint Louis
5. Reichstein M, Camps-Valls G, Stevens B, Jung M, Denzler J, Carvalhais N, Prabhat (2019) Deep learning and process understanding for data-driven earth system science. Nature 566:195–204. https://doi.org/10.1038/s41586-019-0912-1
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