Neural networks are used to predict the performance of fabrics in clothing manufacturing. The predictions are based on fabric mechanical properties measured on the KES-FB system. The influence of the number of input and hidden nodes on the convergence speed and the prediction accuracy are investigated. Tests indicate that these artificial neural networks are effective for predicting potential problems in clothing manufacturing.
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