Application of Soft Computing Techniques to Classification of Licensed Subjects

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Kubalik:2004:basys,

• author = "Jiri Kubalik and Marcel Jirina and Oldrich Stary and Lenka Lhotska and Jan Suchy",
• title = "Application of Soft Computing Techniques to Classification of Licensed Subjects",
• 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",
• year = "2004",
• editor = "Luis M. Camarinha-Matos",
• volume = "159",
• series = "IFIPAICT",
• pages = "481--488",
• address = "27--29 September",
• month = "Vienna, Austria",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-0-387-22829-7",
• DOI = "doi:10.1007/0-387-22829-2_52",
• URL = "https://doi.org/10.1007/0-387-22829-2_52",
• language = "en",
• oai = "oai:CiteSeerX.psu:10.1.1.626.6005",
• 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",
• URL = "http://ida.felk.cvut.cz/cgi-bin/docarc/public.pl/document/82/basys_2004_submission.pdf",
• size = "8 pages",
• 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.",
• notes = "published 2005",

}

Genetic Programming entries for Jiri Kubalik Marcel Jirina Oldrich Stary Lenka Lhotska Jan Suchy

Citations