Application of Soft Computing Techniques to Classification of Licensed Subjects
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Kubalik:2004:basys,
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author = "Jiri Kubalik and Marcel Jirina and Oldrich Stary and
Lenka Lhotska and Jan Suchy",
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title = "Application of Soft Computing Techniques to
Classification of Licensed Subjects",
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booktitle = "Emerging Solutions for Future Manufacturing Systems:
IFP TC 5 / WG 5.5 Sixth IFIP International Conference
on Information Technology for Balanced Automation
Systems in Manufacturing and Services",
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year = "2004",
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editor = "Luis M. Camarinha-Matos",
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volume = "159",
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series = "IFIPAICT",
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pages = "481--488",
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address = "27--29 September",
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month = "Vienna, Austria",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-0-387-22829-7",
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DOI = "doi:10.1007/0-387-22829-2_52",
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URL = "https://doi.org/10.1007/0-387-22829-2_52",
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language = "en",
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oai = "oai:CiteSeerX.psu:10.1.1.626.6005",
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rights = "Metadata may be used without restrictions as long as
the oai identifier remains attached to it.",
-
URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.626.6005",
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URL = "http://ida.felk.cvut.cz/cgi-bin/docarc/public.pl/document/82/basys_2004_submission.pdf",
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size = "8 pages",
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abstract = "This paper presents an application of soft computing
techniques to the construction of decision support tool
used for identifying the economically unstable licensed
subjects. The work has been initiated by the Czech
Energy Regulatory Office whose main mission is to guard
the regular heat supply without significant
disturbances. Thus the main goal is to develop a tool
for automatic identification of the companies that
could cancel the supply due to economic problems
without detailed examination of each company. In order
to achieve the goal two approaches have been chosen.
The first one is based on development of an aggregate
evaluation criterion for assessing the firms. The other
one uses artificial neural networks and multivariate
decision trees induced with genetic programming for
classification of the firms.",
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notes = "published 2005",
- }
Genetic Programming entries for
Jiri Kubalik
Marcel Jirina
Oldrich Stary
Lenka Lhotska
Jan Suchy
Citations