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The viscoplastic behavior of a carbon fiber/polymer matrix composite is investigated via different modeling schemes. The first model is phenomenological in nature based on the overstress‐viscoplasticity. The second model utilizes neural networks paradigms. Genetic algorithm‐based strategies are used to prune the proposed neural network. Several optimization algorithms are implemented for training the network. In comparison, the neurocomputational model is found to outperform the phenomenological model. POLYM. COMPOS., 2009.
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Al‐Haik et al. (2008) studied this question.
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