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Proceedings Paper

Pareto selection of neural network approximation subject to virtual leave-one-out criteria and application to defect centers identification in semi-insulating materials
Author(s): Stanislaw Jankowski; Maciej Ojczyk
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Paper Abstract

Selection of neural networks for function approximation are well known and widely described in many recent papers. This study extends the understanding of the problem on different areas of optimization. Typically selection of best model reduces to searching for models that best fit to leave-one-out criteria. This work joins leave-one-out criteria with genetic algorithms optimization methods and implements it with respect to Pareto optimum. Algorithm constructed in this study basis on presented methods and was applied in semi-insulating materials approximation problem as well as synthetic data models selection.

Paper Details

Date Published: 26 April 2006
PDF: 9 pages
Proc. SPIE 6159, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments IV, 615930 (26 April 2006); doi: 10.1117/12.674865
Show Author Affiliations
Stanislaw Jankowski, Warsaw Univ. of Technology (Poland)
Maciej Ojczyk, Warsaw Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 6159:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments IV

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