Determination of Pigment Combinations for Textile Printing Using Artificial Neural Networks

This paper demonstrates the possibility of using counter-propagation neural networks to identify the combinations of dyes in textile printing paste formulations. An existing collection of 1430 printed samples produced with 10 dyes was used for neural network training. The reflectance values served as input data and the known concentrations of single dye or two dyes were used for printing each sample. Some variations of neural network parameters were tested to determine the best model, and a cross-validation method was used to estimate the generalization error. Also, some modifications of input and output data were made to improve the learning capabilities.