Abstract:

In view of poor practicability of conventinal color matching models of melange yarn, a new method of color matching based on the powerful nonlinear mapping capability of neural network was discussed. In the article, color matching model of melange yarn based on BP neural network was built, the effects of BP algorithms and nodes number of hidden layer on simulative effect and generalization were studied. The results show that, the color matching model of melange yarn based on BP neural network can achieve the nonlinear mapping between the reflectivity of melange yarn and the recipes. The new algorithms such as Levenberg-Marquardt, Quasi-Newton and Conjugate Gradient Algorithms have greater advantages on the iterations and simulation time. And the nodes number of hidden layer has little impact on the result of the simulation. The average predicted color difference DEcmc(2:1) of the training sample is 0.18, but outside the scope of the training sample is bigger, which means the generalization of this color matching model based on BP neural network need to enhance in the further study.