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Highlights

• A machine learning-based approach for fiber-reinforced polypropylene composites design.

• An artificial neural network to predict the load–displacement curves for targeted composite materials.

• Reduce time and effort of the material designers for intelligent product design.

• System identification through sparse identification of nonlinear dynamical systems.

• An approach for smart manufacturing focusing on Industry 4.0.

Details can be found in the following published journal: https://doi.org/10.1016/j.compstruct.2020.113207

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Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing

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