en گروه سرامیک Ceramic Materials and Engineering Research Paper Research Paper Multivariable regression and artificial neural network procedures were used to modeling of the input power and gas holdup of flotation. The stepwise nonlinear equations have shown greater accuracy than linear ones where they can predict input power, and gas holdup with the correlation coefficients of 0.79 thereby 0.51 in the linear, and R2=0.88 versus 0.52 in the non linear, respectively. For increasing accuracy of predictions, Feed-forward artificial neural network (FANN) was applied. FANNs with 2-2-5-5, and 2-2-3-2-2 arrangements, were capable to estimating of the input power and gas holdup, respectively. They were achieved quite satisfactory correlations of 0.96 in testing stage for input power prediction, and 0.64 for gas holdup prediction Flotation, Input Power, Gas Holdup, Regression, Artificial Neural Network 12 19 http://ijmse.iust.ac.ir/browse.php?a_code=A-10-127-71&slc_lang=en&sid=1 B. Shahbazi 180031947532846003001 180031947532846003001 Yes B. Rezai 180031947532846003002 180031947532846003002 No S. Chehreh Chelgani 180031947532846003003 180031947532846003003 No S. M. J. Koleini 180031947532846003004 180031947532846003004 No M. Noaparast 180031947532846003005 180031947532846003005 No