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)
Prediction of Blasting Cost in Limestone Mines Using Gene Expression Programming Model and Artificial Neural Networks
1. Prediction of Blasting Cost in Limestone Mines Using Gene Expression Programming Model and Artificial Neural Networks

R. Bastami; A. Aghajani Bazzazi; H. Hamidian Shoormasti; K. Ahangari

Volume 11, Issue 1 , Winter 2020, , Pages 281-300

http://dx.doi.org/10.22044/jme.2019.9027.1790

Abstract
  The use of blasting cost (BC) prediction to achieve optimal fragmentation is necessary in order to control the adverse consequences of blasting such as fly rock, ground vibration, 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
2. 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 , Autumn 2018, , Pages 917-940

http://dx.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 ...  Read More
Estimation of Cadmium and Uranium in a stream sediment from Eshtehard region in Iran using an Artificial Neural Network
3. Estimation of Cadmium and Uranium in a stream sediment from Eshtehard region in Iran using an Artificial Neural Network

F. Razavi Rad; F. Mohammad Torab; A. Abdollahzadeh

Volume 7, Issue 1 , Winter 2016, , Pages 97-107

http://dx.doi.org/10.22044/jme.2016.500

Abstract
  Considering the importance of Cd and U as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the Eshtehard region ...  Read More
Application of artificial neural network and genetic algorithm to modelling the groundwater inflow to an advancing open pit mine
4. Application of artificial neural network and genetic algorithm to modelling the groundwater inflow to an advancing open pit mine

S. Bahrami; F. Doulati Ardejani

Volume 6, Issue 1 , Winter 2015, , Pages 21-30

http://dx.doi.org/10.22044/jme.2014.330

Abstract
  In this study, a hybrid intelligent model has been designed to predict groundwater inflow to a mine pit during its advance. Novel hybrid method coupling artificial neural network (ANN) ...  Read More
Prediction of recovery of gold thiosulfate on activated carbon using artificial neural networks
5. Prediction of recovery of gold thiosulfate on activated carbon using artificial neural networks

Saeed Alishahi; Ahmad Darban; Mahmood Abdollahi

Volume 5, Issue 1 , Winter 2014, , Pages 55-66

http://dx.doi.org/10.22044/jme.2014.271

Abstract
  Since a high toxicity of cyanide which use as a reagent in the gold processing plant, thiosulfate has been recognized as a environmental friendly reagent for leaching of gold from ore. ...  Read More