<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Kalyani, V. K.</style></author><author><style face="normal" font="default" size="100%">Pallavika</style></author><author><style face="normal" font="default" size="100%">Chaudhuri, Sanjay</style></author><author><style face="normal" font="default" size="100%">Charan, T. Gouri</style></author><author><style face="normal" font="default" size="100%">Haldar, D. D.</style></author><author><style face="normal" font="default" size="100%">Kamal, K. P.</style></author><author><style face="normal" font="default" size="100%">Badhe, Yogesh P.</style></author><author><style face="normal" font="default" size="100%">Tambe, S. S.</style></author><author><style face="normal" font="default" size="100%">Kulkarni, B. D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Study of a laboratory-scale froth flotation process using artificial neural networks</style></title><secondary-title><style face="normal" font="default" size="100%">Mineral Processing and Extractive Metallurgy Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">back propagation algorithm</style></keyword><keyword><style  face="normal" font="default" size="100%">froth flotation</style></keyword><keyword><style  face="normal" font="default" size="100%">laboratory-scale</style></keyword><keyword><style  face="normal" font="default" size="100%">neural network</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">DEC</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">2</style></number><publisher><style face="normal" font="default" size="100%">TAYLOR &amp; FRANCIS INC</style></publisher><pub-location><style face="normal" font="default" size="100%">325 CHESTNUT ST, SUITE 800, PHILADELPHIA, PA 19106 USA</style></pub-location><volume><style face="normal" font="default" size="100%">29</style></volume><pages><style face="normal" font="default" size="100%">130-142</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom3><style face="normal" font="default" size="100%">Foreign</style></custom3><custom4><style face="normal" font="default" size="100%">0.611</style></custom4></record></records></xml>