Neural networks have led to the evolution of the processing methodology of computational sciences. The problems like bio composites modeling and prediction are difficult to model with classical mathematical and statistical tools because of the data inherent noise. NN’s processing capability in the forecasting, recognition, modeling, system analysis and control can give fast characterization, modeling and prediction of bio composites properties, provided as long as datasets are available. Using Matlab®, a neural network model was evaluated to characterize the optimal properties of the ANS reinforced the Polypropylene. The feed forward multilayer model provided best results in comparison with the finite element method and the experimental tensile tests. The trained neural network is able to provide a best prediction of such bio composite based on natural particles having more advantages to the environment, economy and the sustainable development.
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