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The error values of response surface methodology and artificial neural network model were calculated.
The performance of TPGO was further optimized with response surface methodology and artificial neural network (ANN) analysis.
Response surface methodology and artificial neural network were applied for modeling and predicting of the experimental data for catalytic kinetic for the hydrogenation of carbon monoxide.
A mixed information technology is used to solve this problem basing on mathematical modeling, multi-purpose system methodology and artificial neural networks.
Two methods, response surface methodology and artificial neural network were used to predict the tensile strength of friction stir welded AA7039 aluminium alloy.
The aim of this study is to investigate an optimization process for the degradation of total petroleum hydrocarbon (TPH) by a tropical plant, Paspalum scrobiculatum L. Hack, using response surface methodology and artificial neural network.
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The adsorption phenomena were optimized and simulated by using response surface methodology (RS M and artificial neural network (ANN).
The present work describes the comparison of biodiesel yield prediction by Response Surface Methodology (RS M and Artificial Neural Network (ANN).
In this study, an experimental design was used to develop response surface methodology (RS M and artificial neural network (ANN) models.
Response surface methodology (RS M and artificial neural network (ANN) were used to model cultural conditions of curdlan production.
Response surface methodology (RS M and artificial neural network (ANN) approaches were used for modeling the content of fatty acid ethyl esters (FAEE) and optimizing the four process variables.
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