application of genetic algorithm to model and interpret mechanical properties in thermoplastic starch-based biocomposites reinforced by rice straw

In the present study, modeling of mechanical properties of starch/rice straw biocomposites was carried out by the combination of an adaptive neuro-fuzzy inference system (anfis) and a genetic algorithm (ga) method. the three primary material variables including chemical modification of rice straw, filler loading and composition were considered as inputs, and young’s modulus, tensile strength, ultimate strain, and absorbed energy were assumed as the outputs. the developed model of anfis-ga has been found to have a close agreement with the experimental results based on the root mean square error (rmse), squared coefficient of correlation (r2) and mean percentage error (mpe).