DNA-NSGA-II nonlinear dynamic system modeling approach using RBF neural networks
Ning Wang · Journal of Chemical Industry and Engineering · 2007
Based on the operators of DNA computing, a multi-objective non-dominated sorted genetic algorithm(DNA-NSGA-Ⅱ)was proposed to optimize the radial basis function (RBF) network.Both the structure complexity and the approximation performance were optimized.Once a group of Pareto optimal solutions were derived, the appropriate RBF network could be chosen in terms of the sum of absolute values of the testing errors.Simulation results of a continuous stirred tank reactor (CSTR) and pH neutralization process showed that the proposed method is an efficient black box dynamic modeling approach.