Artificial neural network for modeling the size of silver nanoparticles’ prepared in montmorillonite/starch bionanocomposites

In this study, artificial neural network (ANN) was used to develop an approach for evaluation of silver nanoparticles (Ag–NPs) size in the bionanocomposites substrate. A multi-layer feed forward ANN was applied to correlate the output as size of Ag–NPs, with four inputs include of AgNO3 concentration, temperature of reaction, weight percentage of starch, and MMT amount. The results of proposed methodology were compared for its predictive capabilities in terms of coefficient determination (R2) and mean square error (MSE) based on the validation data set. The model finding revealed that AgNO3 concentration content has significant effect on size of Ag–NPs.

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