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Boosted Neural Networks in Evolutionary Computation
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SYSNO ASEP 0333959 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Boosted Neural Networks in Evolutionary Computation Title Neuronové sítě s boostingem v evolučních výpočtech Author(s) Holeňa, Martin (UIVT-O) SAI, RID
Linke, D. (DE)
Steinfeldt, N. (DE)Source Title Neural Information Processing. - Berlin : Springer, 2009 / Leung C.S. ; Lee M. ; Chan J.H. - ISBN 978-3-642-10682-8 Pages s. 131-140 Number of pages 10 s. Action ICONIP 2009. International Conference on Neural Information Processing /16./ Event date 01.12.2009-05.12.2009 VEvent location Bangkok Country TH - Thailand Event type WRD Language eng - English Country DE - Germany Keywords evolutionary algorithms ; empirical objective functions ; surrogate modelling ; surrogate modelling ; artificial neural networks ; boosting Subject RIV IN - Informatics, Computer Science R&D Projects GA201/08/0802 GA ČR - Czech Science Foundation (CSF) GEICC/08/E018 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000279253400015 EID SCOPUS 76249131858 DOI 10.1007/978-3-642-10684-2_15 Annotation The paper deals with a neural-network-based version of surrogate modelling, a modern approach to the optimization of empirical objective functions. The approach leads to a substantial decrease of time and costs of evaluation of the objective function, a property that is particularly attractive in evolutionary optimization. In the paper, an extension of surrogate modelling with regression boosting is proposed, which increases the accuracy of surrogate models, thus also the agreement between results obtained with the model and those obtained with the original objective function. The extension is illustrated on a case study in materials science. Presented case study results clearly confirm the usefulness of boosting for neural-network-based surrogate models. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2010
Number of the records: 1