Comparison of support vector machines (SVMs) and the learning vector quantization (LVQ) techniques for geological domaining: a case study from Darehzar porphyry copper deposit, SE Iran-Reference-Cited by-同舟云学术

Comparison of support vector machines (SVMs) and the learning vector quantization (LVQ) techniques for geological domaining: a case study from Darehzar porphyry copper deposit, SE Iran

Published:2024-08-23 Issue: Volume: Page:
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Abbaszadeh Maliheh,Khosravi Vahid,Pour Amin Beiranvand

Funder

University of Kashan

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s12145-024-01452-x.pdf

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4. Alizadeh Sevari B, Hezarkhani A (2014) Fluid evolution of the magmatic hydrothermal porphyry copper deposit based on fluid inclusion and stable isotope studies at Darrehzar, Iran. ISRN Geol 2014:1–10. https://doi.org/10.1155/2014/865941

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