This study presents a diametric distribution model based on a one-dimensional cellular automata (CA) model and artificial neural network (ANN). Each CA cell proposed stands for a dap class, with the future state being predicted in function of the present state of this cell, the state of its surrounding cells and of its present and future ages. An ANN was used as a rule of evolution. Accuracy was evaluated by applying the statistical procedure L, a relationship between observed and estimated frequency and biological realism of the model built. Of the trained networks, 10 representing diametric distribution evolution with more accuracy were selected. Of these 10 ANR, seven represented estimated values statistically equal to those observed (p>0.01). The focus of the modeling proposed allows estimating future diametric distributions accurately.
Computational intelligence; Artificial neural network; L & O
