@article { ISI:000252354300005,
	title = {Study of a laboratory-scale froth flotation process using artificial neural networks},
	journal = {Mineral Processing and Extractive Metallurgy Review},
	volume = {29},
	number = {2},
	year = {2008},
	month = {DEC},
	pages = {130-142},
	publisher = {TAYLOR \& FRANCIS INC},
	address = {325 CHESTNUT ST, SUITE 800, PHILADELPHIA, PA 19106 USA},
	abstract = {<p>A three-layer feed-forward artificial neural network (ANN) model, trained using the error back propagation algorithm, has been established to simulate the froth flotation process for the beneficiation of coal fines. The network model validates the experimentally observed qualitative and quantitative trends. The optimal model parameters in terms of network weights have been estimated and can be used to compute the parameters of the coal flotation process over wide-ranging experimental conditions.</p>},
	keywords = {back propagation algorithm, froth flotation, laboratory-scale, neural network},
	issn = {0882-7508},
	doi = {10.1080/08827500701421912},
	author = {Kalyani, V. K. and Pallavika and Chaudhuri, Sanjay and Charan, T. Gouri and Haldar, D. D. and Kamal, K. P. and Badhe, Yogesh P. and Tambe, S. S. and Kulkarni, B. D.}
}
