Science and Technology of Nuclear Installations
Volume 2008 (2008), Article ID 681890, 10 pages
doi:10.1155/2008/681890
Research Article
Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
Department of Nuclear Engineering, Polytechnic of Milan, Via Ponzio 34/3, Milan 20133, Italy
Received 2 May 2007; Revised 16 November 2007; Accepted 3 December 2007
Academic Editor: Nikola Cavlina
Copyright © 2008 F. Cadini et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP) for nuclear dynamics are considered in comparison to static modeling by a finite impulse response multilayer perceptron (FIR-MLP) and a conventional static MLP. The comparison is made with respect to the nonlinear dynamics of a nuclear reactor as investigated by IIR-MLP in a previous paper. The superior performance of the locally recurrent scheme is demonstrated.