Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6642733 | Fuel | 2013 | 7 Pages |
Abstract
⺠We predict the pyrite oxidation applying artificial neural networks (AANs). ⺠In comparison to classical techniques, fewer parameters are needed for prediction. ⺠Unlike mathematical models, ANN makes no prior assumptions about data distribution. ⺠Pyrite content remained within the waste particles increases gradually with depth.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Mohammadhossein Sadeghiamirshahidi, Teimour Eslam kish, Faramarz Doulati Ardejani,