Abstract:Aiming to the shortcoming of the traditional prediction model, a method for designing the RBF neural network based on chaotic immune optimization algorithm (CIOA) is proposed, which uses CIOA to the RBF network center vector and weights optimization. By applying chaos mutation operator to producing new antibody and applying immune selection operator to realizing the survival of the fittest, CIOA is able to maintain a good diversity. At the same time, CIOA has higher convergence speed and it can effectively avoid falling into local optima. The results show that chaotic immune optimization RBF neural network applied to the prediction of dynamic deformation, effectively improve the predicted speed and performance.