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The Application of Artificial Neural Network in the Classification of Common Woven Fabrics

The Application of Artificial Neural Network in the Classification of Common Woven Fabrics. Hongbin Jin Shanghai Customs College. Commodity Classification. Fundamental work Mainly performed by people Time-consuming Easy to make mistakes

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The Application of Artificial Neural Network in the Classification of Common Woven Fabrics

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  1. The Application of Artificial Neural Network in the Classification of Common Woven Fabrics Hongbin Jin Shanghai Customs College

  2. Commodity Classification • Fundamental work • Mainly performed by people • Time-consuming • Easy to make mistakes • Objective: predict the classification of common woven fabrics using Artificial Neural Network (ANN)

  3. What is ANN • An ANN is a mathematical model based on biological neural networks. • An ANN is characterized by three things: • Architecture • Activation function • Learning algorithm: Back-Propagation (BP)

  4. A typical ANN architecture

  5. Artificial Neuron Stimulus Response

  6. Activation function

  7. x1 (Dominant fiber): cotton x2 (Content): 60% x3 (Secondary fiber): polyester x4 (Weight): 150g/m2 y1 (Chapter): 52 y2 (Order): 10 Methods Woven fabric, weighing 150g/m2, consisting of 60% cotton and 40% staple fibers of polyester 5210

  8. ANN architectures used • One-hidden-layer containing 18 neurons • Two-hidden-layer containing 8+8 neurons • Two-hidden-layer containing 14+8 neurons

  9. Results and discussion

  10. Prediction results

  11. Thanks for your attention!

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