Neural network modeling to support an experimental study of the delignification process of sugarcane bagasse after alkaline hydrogen peroxide pre-treatment.The present study examines the use of Artificial Neural Networks (ANN) as prediction and fault detection tools for the delignification process of sugarcane bagasse via hydrogen peroxide (H2O2).  Analytical results for the delignification were obtained by Fourier Transform Infrared (FT-IR) analysis and used for the ANN training and testing steps, allowing for the development of ANN models.  An ANN topology was selected for each proposed model, whose performance was evaluated by the correlation coefficient (R2) and error indices (MSE and SSE). 
ANN
Analytical results for the delignification were obtained by Fourier Transform Infrared (FT-IR) analysis and used for the ANN training and testing steps, allowing for the development of ANN models. 
FT-IR