Volume 16 (2025)
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
Targeting of porphyry copper mineralization using a continuous-based logistic function approach in the Varzaghan district, north of Urumieh-Dokhtar magmatic arc

mobin saremi; Abbas Maghsoudi; Reza Ghezelbash; mahyar yousefi; Ardeshir Hezarkhani

Articles in Press, Accepted Manuscript, Available Online from 30 August 2024

https://doi.org/10.22044/jme.2024.14752.2803

Abstract
  Mineral prospectivity mapping (MPM) is a multi-step and complex process designed to narrow down the target areas for exploratory activities in subsequent stages. To pinpoint promising zones of porphyry copper mineralization in the Varzaghan district, NW Iran, various exploration evidence layers were ...  Read More

Exploration
A Comparative Analysis of Artificial Neural Network (ANN) and Gene Expression Programming (GEP) Data-driven Models for Prospecting Porphyry Cu Mineralization; Case Study of Shahr-e-Babak Area, Kerman Province, SE Iran

Bashir Shokouh Saljoughi; Ardeshir Hezarkhani

Volume 15, Issue 2 , April 2024, , Pages 761-790

https://doi.org/10.22044/jme.2023.13852.2573

Abstract
  The porphyry Cu-mineralization potential area studied in this article is located in the southern section of the Central Iranian volcano–sedimentary complex, contains large number of mineral deposits, and occurrences that are currently facing a shortage of resources. Therefore, prospecting potential ...  Read More

Investigation of Geochemical Correlation Between Radioactive and Rare Earth Elements: Case Study of Baghak Mine, NE Iran

Seyyed S. Ghannadpour; A. Hezarkhani

Volume 12, Issue 2 , April 2021, , Pages 569-587

https://doi.org/10.22044/jme.2021.10793.2045

Abstract
  In several uranium (U) prospecting projects in Iran, particularly Central Iran, the association and enrichment of rare earth elements (REEs) are known as the usual features. Sometimes the association of REEs and U with high economic perspective has caused that the relation between the rare earth and ...  Read More

Delineation of Alteration Zones Based on Wavelet Neural Network (WNN) and Concentration–Volume (C-V) Fractal Methods in the Hypogene Zone of Porphyry Copper Deposit, Shahr-e-Babak District, SE Iran

B. Shokouh Saljoughi; A. Hezarkhani

Volume 11, Issue 4 , October 2020, , Pages 1173-1190

https://doi.org/10.22044/jme.2020.10079.1944

Abstract
  In this paper, we aim to achieve two specific objectives. The first one is to examine the applicability of wavelet neural network (WNN) technique in ore grade estimation, which is based on integration between wavelet theory and Artificial Neural Network (ANN). Different wavelets are applied as activation ...  Read More

Exploration
A Comparative Study of SVM and RF Methods for Classification of Alteration Zones Using Remotely Sensed Data

N. Mahvash Mohammadi; A. Hezarkhani

Volume 11, Issue 1 , January 2020, , Pages 49-61

https://doi.org/10.22044/jme.2019.7956.1664

Abstract
  Identification and mapping of the significant alterations are the main objectives of the exploration geochemical surveys. The field study is time-consuming and costly to produce the classified maps. Therefore, the processing of remotely sensed data, which provide timely and multi-band (multi-layer) data, ...  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

Exploitation
Application of fractal modeling to delineate alteration zones and lithological units in Masjed-Daghi Cu-Au porphyry deposit, NW Iran

H. Nikoogoftar Safa; A. Hezarkhani

Volume 10, Issue 2 , April 2019, , Pages 339-356

https://doi.org/10.22044/jme.2018.7071.1550

Abstract
  In this paper, we aim to present a quantitative modeling for delineating the alteration zones and lithological units in the hypogene zone of Masjed-Daghi Cu-Au porphyry deposit (NW Iran) based on the drill core data. The main goal of this work is to apply Ordinary Kriging (OK) and concentration-volume ...  Read More

Environment
Identification of geochemical anomalies associated with Cu mineralization by applying spectrum-area multi-fractal and wavelet neural network methods in Shahr-e-Babak mining area, Kerman, Iran

B. Shokouh Saljoughi; A. Hezarkhani

Volume 10, Issue 1 , January 2019, , Pages 49-73

https://doi.org/10.22044/jme.2018.6949.1533

Abstract
  The Shahr-e-Babak district, as the studied area, is known for its large Cu resources. It is located in the southern side of the Central Iranian volcano–sedimentary complex in SE Iran. Shahr-e-Babak is currently facing a shortage of resources, and therefore, mineral exploration in the deeper and ...  Read More

A comparison between knowledge-driven fuzzy and data-driven artificial neural network approaches for prospecting porphyry Cu mineralization; a case study of Shahr-e-Babak area, Kerman Province, SE Iran

B. Shokouh Saljoughi; A. Hezarkhani; E. Farahbakhsh

Volume 9, Issue 4 , October 2018, , Pages 917-940

https://doi.org/10.22044/jme.2018.6752.1495

Abstract
  The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become ...  Read More

Environment
A comparative study of fractal models and U-statistic method to identify geochemical anomalies; case study of Avanj porphyry system, Central Iran

B. Shokouh Saljoughi; A. Hezarkhani; E. Farahbakhsh

Volume 9, Issue 1 , January 2018, , Pages 209-227

https://doi.org/10.22044/jme.2017.6120.1426

Abstract
  The most significant aspect of a geochemical exploration program is to define and separate the anomalous values from the background. In the past decades, geochemical anomalies have been identified by means of various methods. Most of the conventional statistical methods aiming at defining the geochemical ...  Read More

Selection of new exploration targets using lithogeochemical data obtained for Taknar deposit located in NE of Iran

Kh. Maroufi Naghadehi; A. Hezarkhani; K. Seifpanahi Shabani

Volume 6, Issue 1 , January 2015, , Pages 11-20

https://doi.org/10.22044/jme.2015.370

Abstract
  Taknar deposit is located about 28 km to the north-west of Bardaskan in the Khorasan-e-Razavi province, which is situated in the north-eastern part of Iran. This deposit is unique, formed within the Taknar formation in the Ordovician time. As a result, it is of much interest to many researchers working ...  Read More