Prediction of the Amount of Wood Using Neural Networks

Coniferous trees such as eucalyptus used to be preferred for papermaking because the cellulose fiber in the pulp of these species are longer, therefore making for stronger paper. In this study, the proposed neural network method solves in an efficient way, how to build prediction models in engineering. The system has been applied to predict amount of wood for production of paper, in which the coefficients can explain the variable with more influence over the variable to forecast. Obtaining a good prediction and as simple as possible, i.e. with the least number of forecast variables.