Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics
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 th...
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| Format: | Article |
| Language: | English |
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Wiley
2008-01-01
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| Series: | Science and Technology of Nuclear Installations |
| Online Access: | http://dx.doi.org/10.1155/2008/681890 |
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| _version_ | 1832545619114196992 |
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| author | F. Cadini E. Zio N. Pedroni |
| author_facet | F. Cadini E. Zio N. Pedroni |
| author_sort | F. Cadini |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-0048127a13374743b92cd42c0aa6724b |
| institution | Kabale University |
| issn | 1687-6075 1687-6083 |
| language | English |
| publishDate | 2008-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Science and Technology of Nuclear Installations |
| spelling | doaj-art-0048127a13374743b92cd42c0aa6724b2025-02-03T07:25:09ZengWileyScience and Technology of Nuclear Installations1687-60751687-60832008-01-01200810.1155/2008/681890681890Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear DynamicsF. Cadini0E. Zio1N. Pedroni2Department of Nuclear Engineering, Polytechnic of Milan, Via Ponzio 34/3, Milan 20133, ItalyDepartment of Nuclear Engineering, Polytechnic of Milan, Via Ponzio 34/3, Milan 20133, ItalyDepartment of Nuclear Engineering, Polytechnic of Milan, Via Ponzio 34/3, Milan 20133, ItalyArtificial 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.http://dx.doi.org/10.1155/2008/681890 |
| spellingShingle | F. Cadini E. Zio N. Pedroni Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics Science and Technology of Nuclear Installations |
| title | Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics |
| title_full | Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics |
| title_fullStr | Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics |
| title_full_unstemmed | Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics |
| title_short | Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics |
| title_sort | validation of infinite impulse response multilayer perceptron for modelling nuclear dynamics |
| url | http://dx.doi.org/10.1155/2008/681890 |
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