By Kenji Suzuki, editor
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Additional resources for Artificial neural networks - industrial and control engineering applications
Applications to Chemical Processing Author Journal No Title Study Area 30 Artificial Neural Networks - Industrial and Control Engineering Applications 35 A Hybrid Neural Hu et al. Textile 2009 79(14), Network and Immune Research 1319-1330. Algorithm Approach Journal for Fit Garment Design Limitations model to fit inputoutput data more accurately with enhanced classification ability. to predict the fit of For future the garments and research search optimal directions, the sizes dataset needs to be enriched.
They selected blend ratio, yarn count and the rotor speed as input parameters and unevenness of the yarns as output parameter. 0 respectively in this study. 077) were identical. 73 for the ANN and statistical model respectively. Contrary to general opinion of the more reliable prediction of ANN than statistical models, they reported that statistical model developed was more reliable than ANN and by increasing the number of experiments, prediction performance of ANN would increase (Demiryurek & Koc, 2009).
To detect the outlier in the training set, the scaled outlier probability was introduced to increase its robustness. All nonwoven samples were classified into five grades according to visual qualities (such as surface uniformity, the condition of pilling, wrinkles and defects). Each image was individually normalized to zero mean and Artificial Neural Network Prosperities in Textile Applications 45 unit variance before wavelet transform. , 2010). 5 Cloth defects Quality inspection of garments is an important aspect of clothing manufacturing.
Artificial neural networks - industrial and control engineering applications by Kenji Suzuki, editor