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Application of Big Data Mining, Machine Learning and Artificial Intelligence in Geoscience, 2nd Edition

This special issue belongs to the section “Mineral Exploration Methods and Applications“.

Special Issue Information

Dear Colleagues,

Big data and machine learning have brought the study of geoscience onto the artificial intelligence research stage. Big data mining, machine learning and artificial intelligence algorithms and models have been applied to study multi-scale and multi-type geoscientific observation and exploration. The goal of this Special Issue is to highlight recent progress in the research and applications of big data and machine learning in the field of geoscience.

Prof. Dr. Yongzhang Zhou
Prof. Dr. Hui Yang
Dr. Xiaohui Ji
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Minerals is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • artificial intelligence
  • big data mining
  • mineral
  • petrologic geology
  • ore deposit
  • mineral resources prediction
  • remote sensing
  • geochemical exploration

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Published Papers

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Minerals - ISSN 2075-163X