基于PSO算法的RBFNN在织物染色配色中的应用

Application of Particle Swarm Optimization Algorithm Based on RBF Neural Network in Textile Dyeing Color Matching

为了提高计算机配色的效率,提出了一种基于粒子群优化算法(Particle Swarm Optimization algorithm)的RBFNN(radial base function neural network)解决织物染色配色问题的模型。该模型容易实现,没有过多参数需要调整,并且提高了模型的收敛速度和精确度。仿真结果表明,用PSO算法优化的RBF神经网络解决计算机织物染色配色问题是一种较好的方法。

In order to improve the efficiency of computer color matching, a model for textile dyeing color matching with radial base function neural network based on Particle Swarm Optimization Algorithm was proposed in this paper. This model is easy to be realized, with few parameters needing to be adjusted, and meanwhile the convergence speed and accuracy are improved. The simulating results verify that RBF neural network based on Particle Swarm Optimization Algorithm is a good method in textile dyeing color matching.