Research on Ink Color Matching based on Stearns Noechel and BBO Optimization Algorithm

Abstract

With the advancement of industrial informatization, the intelligent reform of printing industry is imperative. In order to improve the efficiency and quality of printing ink color matching, the basic model of BP neural network is optimized and improved by using Stearns noechel algorithm and BBO algorithm, and an intelligent ink color matching model based on Stearns noechel and BBO is constructed. The simulation results show that the average prediction error rate of the intelligent color matching model based on Stearns noechel and BBO is 3.2%, which is lower than 15.3% of K-M theory and 7.9% of BP neural network. After optimization and improvement, the prediction error of the model is reduced by 4.7% compared with the basic model of BP neural network, and the prediction performance is significantly improved, It provides a new computer intelligent color matching scheme for ink color matching of printing enterprises, improves the performance and accuracy of ink color matching, has practicability and optimization, and has important practical significance for the intelligent development of printing industry.