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)
Developing new models for flyrock distance assessment in open-pit mines

Hasel Amini Khoshalan; Jamshid Shakeri; Hesam Dehghani; Kennedy Onyelowe; Marc Bascompta

Articles in Press, Accepted Manuscript, Available Online from 28 April 2022


  In this research work, a comprehensive study is conducted to predict flyrock as a typical and undesirable phenomenon occurring during the blasting operation in open-pit mining. Despite the availability of several empirical methods for predicting the flyrock distance, the complexity of flyrock analysis ...  Read More

Mine Economic and Management
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 , January 2020, , Pages 281-300


  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 air blast in open-pit mines. In this research work, BC is predicted through collecting 146 blasting data from six limestone ...  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


  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

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 , January 2016, , Pages 97-107


  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 in Iran by means of a developed artificial neural network (ANN) model. The forward selection (FS) method is used to select ...  Read More

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 , January 2015, , Pages 21-30


  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) with genetic algorithm (GA) called ANN-GA, was utilised. Ratios of pit depth to aquifer thickness, pit bottom radius ...  Read More

Prediction of recovery of gold thiosulfate on activated carbon using artificial neural networks

Saeed Alishahi; Ahmad Darban; Mahmood Abdollahi

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


  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. After gold leaching process it's important for recovery of gold from solution using adsorption or extraction methods, ...  Read More