A prediction algorithm based on self-organizing fuzzy neural networks

The dyeing process in the cloth-weaving works is a complex chemical reaction. It is a complex nonlinear multi-variable problem to predict the success rate of dyeing since it is affected by many factors. A new prediction algorithm based on structure-adaptive self-organizing fuzzy network is proposed in this paper, which combines supervised competitive learning algorithm with node generation method. The algorithm can adjust both structure and the weights according to the change of environment. Besides, Fuzzy synthesis prediction mechanism is introduced into the algorithm to improve the precision and stability of prediction. Digital Simulations show that the algorithm is effective and suitable for larger scale prediction problem.