Colorant Formulation Using 3 - layer Artificial Neural Networks  

作　　者：忻浩忠 

出　　处：《Journal of China Textile University(English Edition)》1999年第1期43-48,共6页

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.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.

关 键 词：COLORANT FORMULATION artificial NEURAL networks backpropagation NEURAL NETWORK TRAINING NEURAL NETWORK testing. 

分 类 号：TS193[轻工技术与工程—纺织化学与染整工程] TP[轻工技术与工程—纺织科学与工程]