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The Application of Artificial Neural Network in the Classification of Common Woven Fabrics Hongbin Jin Shanghai Customs College
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2 Commodity Classification b Fundamental work b Mainly performed by people Time-consumingTime-consuming Easy to make mistakesEasy to make mistakes b Objective: predict the classification of common woven fabrics using Artificial Neural Network (ANN)
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3 What is ANN b b An ANN is a mathematical model based on biological neural networks. b b An ANN is characterized by three things: 1. 1.ArchitectureArchitecture 2. 2.Activation functionActivation function 3. 3.Learning algorithm: Back-Propagation (BP)
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4 A typical ANN architecture
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5 Artificial Neuron Stimulus Response
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6 Activation function
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7 Methods Woven fabric, weighing 150g/m 2, consisting of 60% cotton and 40% staple fibers of polyester 5210 x1 (Dominant fiber): cotton x2 (Content): 60% x3 (Secondary fiber): polyester x4 (Weight): 150g/m 2 y1 (Chapter): 52 y2 (Order): 10
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8 ANN architectures used b One-hidden-layer containing 18 neurons b Two-hidden-layer containing 8+8 neurons b Two-hidden-layer containing 14+8 neurons
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9 Results and discussion
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10 Prediction results Neural networkOutputs Predictions 12345678 One-hidden- layer (18) y1y1 50.00651.01351.98753.97254.9995554.99955 y2y2 711.48112.5077.000811.76514.51514.76416 Heading500751115213540755125515 5516 Two-hidden- layer (8+8) y1y1 5051.004525455 y2y2 711.99611.7267.001712.00414.89314.94616 Heading500751125212540755125515 5516 Two-hidden- layer (14+8) y1y1 5050.99951.99954.00154.99955 y2y2 7.000611.99911.9857.001312.00213.99615.00215.997 Heading50075112521254075512551455155516 Target outputs50075112521254075512551455155516
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11 Thanks for your attention!
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