In this study, pretreatment of sugarcane bagasse and subsequent enzymatic hydrolysis is investigated using two categories of pretreatment methods: dilute acid (DA) pretreatment and combined DA ozonolysis (DAO) method. Both methods are accomplished at different solid ratios, sulfuric acid concentrations, autoclave residence times, bagasse moisture content, and ozonolysis time. The results show that the DAO pretreatment can significantly increase the production of glucose compared to DA method. Applying k-fold cross validation method, two optimal artificial neural networks (ANNs) are trained for estimations of glucose concentrations for DA and DAO pretreatment methods. Comparing the modeling results with experimental data indicates that the proposed ANNs have good estimation abilities. (C) 2013 Elsevier Ltd. All rights reserved.