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A Nonlinear Black-Box Modelling Methodology for Neural Networks

Authors
  • Cloarec, Guy-Michel
  • Ringwood, John
Publication Date
May 26, 2021
Source
HAL-INRIA
Keywords
Language
English
License
Unknown
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Abstract

The aim of this paper is to present a nonlinear black-box modelling methodology that, in a general context, introduces the use of various statistical techniques to improve the modelling performance. The improvements are obtained by addressing the main problem that any black-box technique is confronted with: the optimal choice of a model topology and the related parameters with respect to the complexity of the problem. The main idea is to efficiently combine statistical resampling and analysis with preprocessing, optimal topology determination, supervised parameter optimization and ensemble techniques.

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