International Journal of Nonferrous Metallurgy

International Journal of Nonferrous Metallurgy

ISSN Print: 2168-2054
ISSN Online: 2168-2062
www.scirp.org/journal/ijnm
E-mail: ijnm@scirp.org
"Estimation of Copper and Molybdenum Grades and Recoveries in the Industrial Flotation Plant Using the Artificial Neural Network"
written by Ebrahim Allahkarami, Omid Salmani Nuri, Aliakbar Abdollahzadeh, Bahram Rezai, Mostafa Chegini,
published by International Journal of Nonferrous Metallurgy, Vol.5 No.3, 2016
has been cited by the following article(s):
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[3] Comparison of Various Estimation and Simulation Methods for Orebody Grade Variations Modeling
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[4] Depression of pyrite in polymetallic sulfide flotation using chitosan-grafted-polyacrylamide polymers
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[5] Mineralogical Prediction on the Flotation Behavior of Copper and Molybdenum Minerals from Blended Cu–Mo Ores in Seawater
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[6] Selectivity index and separation efficiency prediction in industrial magnetic separation process using a hybrid neural genetic algorithm
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[7] Estimation and Improvement of Recovery of Low Grade Copper Oxide Using Sulfide Activation Flotation Method Based on GA–BPNN
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[8] Prediction of flotation efficiency of metal sulfides using an original hybrid machine learning model
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[9] Hyperspectral signature analysis using neural network for grade estimation of copper ore
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[10] Development of a Predictive Model for the Recovery of Rare Earth Elements from the Leaching Process of Chilean Ores
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[11] Mitigation of environmental hazards of sulfide mineral flotation with an insight into froth stability and flotation performance
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[12] Analysis of kinetic models for chalcopyrite flotation: effect of operating parameters
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[13] Учредители: Институт горного дела им. НА Чинакала СО РАН, Сибирское отделение РАН
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