Nuclear Reactor Dynamics On-line Estimation By Locally Recurrent Neural Networks

摘要

In this paper, the Causal Recursive Back-Propagation (CRBP) algorithm is employed to train on-line an Infinite Impulse Response-Locally Recurrent Neural Network (IIR-LRNN) for modelling the dynamics of a next-generation nuclear reactor. The results demonstrate the advantages of the on-line training over the batch-mode learning in the reconstruction of complex nonlinear dynamic relationships.