Abstract:A computational methodology based on inverse modeling and metaheuristics is presented for determining the best parameters of kinetic models aimed to predict the behavior of biomass depolymerization processes during size scaling up. The Univariate Marginal Distribution algorithm, particle swarm optimization, and Interior-Point algorithm were applied to obtain the values of the kinetic parameters (KM and Vmax) of four mathematical models based on the Michaelis–Menten equation: (i) Traditional Michaelis–Menten, (… Show more
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