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A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications

文献类型：期刊论文

作者He, Yuyang9,10; Zhou, You7,8; Wen, Tao6; Zhang, Shuang5; Huang, Fang4; Zou, Xinyu3; Ma, Xiaogang2; Zhu, Yueqin1
刊名APPLIED GEOCHEMISTRY
出版日期2022-05-01
卷号140页码:13
ISSN号0883-2927
关键词LIBS XAFS Mapping Water soil prediction Molecular machine learning Reactive-transport modeling
DOI10.1016/j.apgeochem.2022.105273
通讯作者He, Yuyang(yhe@mail.iggcas.ac.cn)
英文摘要The development of analytical and computational techniques and growing scientific funds collectively contribute to the rapid accumulation of geoscience data. The massive amount of existing data, the increasing complexity, and the rapid acquisition rates require novel approaches to efficiently discover scientific stories embedded in the data related to geochemistry and cosmochemistry. Machine learning methods can discover and describe the hidden patterns in intricate geochemical and cosmochemical big data. In recent years, considerable efforts have been devoted to the applications of machine learning methods in geochemistry and cosmochemistry. Here, we review the main applications including rock and sediment identification, digital mapping, water and soil quality prediction, and deep space exploration. Research method improvements, such as spectroscopy interpretation, numerical modeling, and molecular machine learning, are also discussed. Based on the up-to-date machine learning/deep learning techniques, we foresee the vast opportunities of implementing artificial intelligence and developing databases in geochemistry and cosmochemistry studies, as well as communicating geochemists/ cosmochemists and data scientists.
WOS关键词INDUCED BREAKDOWN SPECTROSCOPY ; REACTIVE TRANSPORT MODELS ; UNDISCOVERED MINERAL-DEPOSITS ; ARTIFICIAL NEURAL-NETWORKS ; SUPPORT VECTOR MACHINE ; RANDOM FOREST ; CENTRAL VALLEY ; WATER-QUALITY ; THEORETICAL CALCULATION ; ISOTOPE FRACTIONATIONS
资助项目National Science Foundation of China (NSFC)[42150202] ; National Science Foundation of China (NSFC)[4217030170] ; China Postdoctoral Science Foundation[2019M660811] ; pre-research project on Civil Aerospace Technologies of China National Space Administration[D020203] ; NSFC[41973063] ; NSFC[42011530431] ; Earth Science Information Partners Lab Grant[05088] ; NSFC project[42003021] ; NSFC project[2126315] ; U.S. National Science Foundation (NSF)[41872253]
WOS研究方向Geochemistry & Geophysics
语种英语
WOS记录号WOS:000799841900004
资助机构National Science Foundation of China (NSFC) ; China Postdoctoral Science Foundation ; pre-research project on Civil Aerospace Technologies of China National Space Administration ; NSFC ; Earth Science Information Partners Lab Grant ; NSFC project ; U.S. National Science Foundation (NSF)
源URL[http://dspace.imech.ac.cn/handle/311007/89573]  
专题力学研究所_高温气体动力学国家重点实验室
通讯作者He, Yuyang
作者单位1.Minist Emergency Management Peoples Republ China, Natl Inst Nat Hazards, Beijing 100085, Peoples R China
2.Univ Idaho, Comp Sci Dept, 875 Perimeter Dr, MS 1010, Moscow, ID 83844 USA
3.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Mineral Resources, Beijing 100029, Peoples R China
4.CSIRO Mineral Resources, Kensington, WA 6151, Australia
5.Texas A&M Univ, Dept Oceanog, College Stn, TX 77843 USA
6.Syracuse Univ, Dept Earth & Environm Sci, Syracuse, NY 13244 USA
7.CAS Ctr Excellence Comparat Planetol, Hefei 230026, Peoples R China
8.Chengdu Univ Technol, Coll Earth Sci, Int Res Ctr Planetary Sci, 61005, Chengdu, Peoples R China
9.Chinese Acad Sci, Inst Mech, State Key Lab High Temp Gas Dynam, Beijing 100190, Peoples R China
10.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Earth & Planetary Phys, Beijing 100029, Peoples R China
推荐引用方式
GB/T 7714		 He, Yuyang,Zhou, You,Wen, Tao,et al. A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications[J]. APPLIED GEOCHEMISTRY,2022,140:13.
APA He, Yuyang.,Zhou, You.,Wen, Tao.,Zhang, Shuang.,Huang, Fang.,...&Zhu, Yueqin.(2022).A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications.APPLIED GEOCHEMISTRY,140,13.
MLA He, Yuyang,et al."A review of machine learning in geochemistry and cosmochemistry: Method improvements and applications".APPLIED GEOCHEMISTRY 140(2022):13.

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来源：力学研究所

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