How multi-objective genetic algorithms handle lack of data, sparse data and excess data: evaluation of some recent case studies in the materials domain.
N. Chakraborti. Stat. Anal. Data Min., 1 (5):
322-328(2009)
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%0 Journal Article
%1 journals/sadm/Chakraborti09
%A Chakraborti, Nirupam
%D 2009
%J Stat. Anal. Data Min.
%K dblp
%N 5
%P 322-328
%T How multi-objective genetic algorithms handle lack of data, sparse data and excess data: evaluation of some recent case studies in the materials domain.
%U http://dblp.uni-trier.de/db/journals/sadm/sadm1.html#Chakraborti09
%V 1
@article{journals/sadm/Chakraborti09,
added-at = {2023-09-30T00:00:00.000+0200},
author = {Chakraborti, Nirupam},
biburl = {https://www.bibsonomy.org/bibtex/25afa209cd2f3f95ecf2540fd6d864828/dblp},
ee = {https://doi.org/10.1002/sam.10025},
interhash = {e4fe56439c83fc654aa254dd3a260ee0},
intrahash = {5afa209cd2f3f95ecf2540fd6d864828},
journal = {Stat. Anal. Data Min.},
keywords = {dblp},
number = 5,
pages = {322-328},
timestamp = {2024-04-09T05:38:31.000+0200},
title = {How multi-objective genetic algorithms handle lack of data, sparse data and excess data: evaluation of some recent case studies in the materials domain.},
url = {http://dblp.uni-trier.de/db/journals/sadm/sadm1.html#Chakraborti09},
volume = 1,
year = 2009
}
