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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9. References
Beneš, M., Starý, O.: Risk Ranking and Selection of Licensed Subjects. In: New Challenges for Energy Decision Makers [CD-ROM]. Cleveland: IAEE, vol. 1, 2003.
Quinlan, J.R. Induction of decision trees. Machine Learning, 1, pp. 81–106, 1986.
Brodley, C.E., Utgoff, P.E. Multivariate decision trees. Machine Learning, 19, pp. 45–77, 1995.
Koza, J. Genetic Programming: on the programming of computers by means of natural selection. Cambridge, MA: The MIT Press, 1992.
Bot, M.C.J., Langdon, W.B. Application of genetic programming to induction of linear classification trees. Proceedings of EuroGP 2000, LNCS 1802, pp. 247–258. Springer, 2000.
Bishop, C. M. Neural Networks for Pattern Recognition. Oxford University Press, New York, 1995.
Rojas, R. Neural Networks: A Systematic Introduction. Springer-Verlag, Berlin, Heidelberg, 1996.
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Kubalík, J., Jiřina, M., Stary, O., Lhotská, L., Suchý, J. (2005). Application of Soft Computing Techniques to Classification of Licensed Subjects. In: Camarinha-Matos, L.M. (eds) Emerging Solutions for Future Manufacturing Systems. BASYS 2004. IFIP International Federation for Information Processing, vol 159. Springer, Boston, MA. https://doi.org/10.1007/0-387-22829-2_52
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DOI: https://doi.org/10.1007/0-387-22829-2_52
Publisher Name: Springer, Boston, MA
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