Prediction of the metallurgical performances of a batch flotation system by image analysis and neural networks-Reference-Cited by-同舟云学术

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Prediction of the metallurgical performances of a batch flotation system by image analysis and neural networks

Published:2014-12 Issue: Volume:69 Page:137-145
ISSN:0892-6875
Container-title:Minerals Engineering
language:en
Short-container-title:Minerals Engineering

Author:

Jahedsaravani A.,Marhaban M.H.,Massinaei M.

Publisher

Elsevier BV

Subject

Mechanical Engineering,Geotechnical Engineering and Engineering Geology,General Chemistry,Control and Systems Engineering

Reference32 articles.

1. Relationship between surface froth features and process conditions in the batch flotation of a sulphide ore;Aldrich;Miner. Eng.,1997

2. Online monitoring and control of froth flotation systems with machine vision: a review;Aldrich;Int. J. Miner. Process.,2010

3. Interpretation of the effect of froth structure on the performance of froth flotation using image analysis;Banford;Powder Technol.,1998

4. Control alternatives for flotation columns;Bergh;Miner. Eng.,1993

5. Prediction of complex sulfide flotation performances by a combined 3D fractal and colour analysis of the froths;Bonifazi;Miner. Eng.,2000

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