| Colorant Formulation Using 3 - layer Artificial Neural Networks |
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| 作者姓名： | 忻浩忠 |
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| 作者单位： | John H. XinInstitute of Textiles & Clothing，The Hong Kong Polytechnic University，Hong Kong |
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| 摘 要： | The colorant formulation using artificial neural networks (ANN) was investigated in this study. A simple 3 -layer, input - hidden - output system was constructed for the recipe formulation of one - , two - , and three -dye mixtures. Comprehensive tests were carried out to explore the properties of a 3 - layer simple ANN systematically . These properties include number of neurons in the hidden layer, learning rate of the network, momentum factor of the network, as well as the number of epochs for the learning process. The tests show accurate results for one - and two - dye mixtures while less accurate but comparable results to conventional colorant formulation systems for three - dye mixtures. It is also found that the optimum values of the neural network parameters are important towards the accuracy of the colorant formulation.
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Colorant Formulation Using 3 - layer Artificial Neural Networks |
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| John H. XinInstitute of Textiles & Clothing,The Hong Kong Polytechnic University,Hong Kong.Colorant Formulation Using 3 - layer Artificial Neural Networks[J].Journal of Donghua University,1999(1). |
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| Authors: | John H XinInstitute of Textiles & Clothing The Hong Kong Polytechnic University Hong Kong |
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| Abstract: | The colorant formulation using artificial neural networks (ANN) was investigated in this study. A simple 3 -layer, input - hidden - output system was constructed for the recipe formulation of one - , two - , and three -dye mixtures. Comprehensive tests were carried out to explore the properties of a 3 - layer simple ANN systematically . These properties include number of neurons in the hidden layer, learning rate of the network, momentum factor of the network, as well as the number of epochs for the learning process. The tests show accurate results for one - and two - dye mixtures while less accurate but comparable results to conventional colorant formulation systems for three - dye mixtures. It is also found that the optimum values of the neural network parameters are important towards the accuracy of the colorant formulation. |
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| Keywords: | colorant formulation artificial neural networks backpropagation neural network training neural network testing |
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