Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks

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SYSNO	0389195
Title	Surrogate Model for Mixed-Variables Evolutionary Optimization Based on GLM and RBF Networks
Author(s)	Bajer, Lukáš (UIVT-O)_{SAI, RID, ORCID} Holeňa, Martin (UIVT-O)_{SAI, RID}
Source Title	SOFSEM 2013. Theory and Practice of Computer Science. S. 481-490. - Berlin : Springer, 2013 / van Emde Boas P. ; Groen F.C.A. ; Italiano G.F. ; Nawrocki J. ; Sack H.
Conference	SOFSEM 2013. Conference on Current Trends in Theory and Practice of Computer Science /39./, Špindlerův Mlýn, 26.01.2013-31.01.2013
Document Type	Konferenční příspěvek (zahraniční konf.)
Grant	GAP202/11/1368 GA ČR - Czech Science Foundation (CSF)
	GA201/08/0802 GA ČR - Czech Science Foundation (CSF)
	278511/2011, CZ - Czech Republic
Institutional support	UIVT-O - RVO:67985807
Language	eng
Country	DE
Keywords	surrogate modelling * RBF networks * genetic algorithms * mixed-variables optimization * continuous and discrete variables
Permanent Link	http://hdl.handle.net/11104/0218075

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Number of the records: 1