Volume 15 (2024)
Volume 14 (2023)
Volume 13 (2022)
Volume 12 (2021)
Volume 11 (2020)
Volume 10 (2019)
Volume 9 (2018)
Volume 8 (2017)
Volume 7 (2016)
Volume 6 (2015)
Volume 5 (2014)
Volume 4 (2013)
Volume 3 (2012)
Volume 2 (2011)
Volume 1 (2010)
Exploration
Identification of Alteration Zones using ASTER Data for Metallic Mineralization in Ahar region, NW Iran

F. Mirsepahvand; M.R. Jafari; P. Afzal; M. A. Arian

Volume 13, Issue 1 , January 2022, , Pages 309-324

https://doi.org/10.22044/jme.2022.11477.2135

Abstract
  The goal of this research work is to recognize the metallic mineralization potential in the Ahar 1:100,000 sheet (NW Iran) using the remote sensing data based on determination of the alteration zones. This area is located in the Ahar-Arasbaran metallogenic zone as a significant metallogenic zone in Iran ...  Read More

Environment
Delineation of alteration zones based on artificial neural networks and concentration-volume fractal methods in the hypogene zone of porphyry copper-gold deposit, Masjed-Daghi, East Azerbaijan Province, Iran

H. Nikoogoftar; A. Hezarkhani

Volume 10, Issue 4 , October 2019, , Pages 883-901

https://doi.org/10.22044/jme.2019.7948.1663

Abstract
  In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of the Artificial Neural Networks (ANNs) technique in ore grade estimation. Different training algorithms and numbers of hidden neurons are applied to estimate Cu grade of borehole data in the hypogene ...  Read More

Exploitation
Delineation of alteration zones based on kriging, artificial neural networks, and concentration–volume fractal modelings in hypogene zone of Miduk porphyry copper deposit, SE Iran

O. Gholampour; A. Hezarkhani; A. Maghsoudi; M. Mousavi

Volume 10, Issue 3 , July 2019, , Pages 575-595

https://doi.org/10.22044/jme.2018.7104.1558

Abstract
  This paper presents a quantitative modeling for delineating alteration zones in the hypogene zone of the Miduk porphyry copper deposit (SE Iran) based on the core drilling data. The main goal of this work was to apply the Ordinary Kriging (OK), Artificial Neural Networks (ANNs), and Concentration-Volume ...  Read More