Cross Section Expression Based on Neural Network Algorithm

n order to obtain the cross sections in different operating conditions affected by the thermal parameters and depletion, the neural network algorithm was used for function approximation. Bayesian normalization function and the early termination method were used to train sample cross section. Further more, this method was tested by the two examples. By comparing with FITLINK, the results show that cross section expression based on neural network algorithm is feasible.