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Building decision trees based on production knowledge as support in decision-making process

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Języki publikacji
EN
Abstrakty
EN
The article presents sources of production knowledge and thoroughly describes its identification which on the construction of decision trees, and on the construction of knowledge bases for production processes. The problems that arise during the technical preparation of production are briefly characterized and the advanced algorithm with which decision trees can be built is described in detail. A decision tree was built based on real data from the manufacturing company. Decision trees are presented as a method of knowledge representation.
Rocznik
Strony
36--40
Opis fizyczny
Bibliogr. 14 poz., rys., tab.
Twórcy
  • University of Bielsko-Biala, ul. Willowa 2, 43-309 Bielsko-Biala, Poland
Bibliografia
  • 1.Cichosz, P., 2000. Learning systems, WNT, Warszawa.
  • 2.Dai1, W., Ji, W., 2014. A MapReduce Implementation of C4.5 Decision Tree Algorithm, International Journal of Database Theory and Application, 7(1), 49-60.
  • 3.Gorski, F., Zawadzki, P., Hamrol, A., 2016. Knowledge based engineering as a condition of effective mass production of configurable products by design automation, Journal of Machine Engineering, 16(4), 5-30.
  • 4.Hssina, B., Merbouha, A., Ezzikouri, H., Erritali M., 2014. A comparative study of decision tree ID3 and C4.5 International Journal of Advanced Computer Science and Applications, Special Issue on Advances in Vehicular Ad Hoc Networking and Applications, 13-18.
  • 5.Jedrzejewski, J., Kwasny, W., 2015. Development of Machine Tool Operational Properties, Journal of Machine Engineering, 15(1), 5-26.
  • 6.Kowalczyk, A., Nogalski, B., 2007. Management of knowledge. Concept and tools., Print DIFIN, Warszawa.
  • 7.Kutschenreiter-Praszkiewicz, I., 2012. Application of knowledge based systems in technical production preparation of machine parts, Wydawnictwo Naukowe Akademii Techniczno-Humanistycznej w Bielsku-Białej, Bielsko-Biała.
  • 8.Kutschenreiter-Praszkiewicz, I., 2018. Machine learning in SMED, Journal of Machine Engineering, 18(2), 31-40.
  • 9.Matuszny, M., 2019. Proccesing and identification of production knowledge for knowledge base build for production processes Technology, processes and production systems, 3, 115-125.
  • 10.Paszek, A., 2011. Construction of knowledge management system in a production company. Part II: Example Enterprise Management, 1, 35-43.
  • 11.Rokach, L., Maimon, O., 2008. Data mining with decision trees, Singapore, 69, 71-79.
  • 12.Rojek, I., 2017. Expert system for selection of semi-finished products using the decision trees, Studies & Proceedings of Polish Association for Knowledge Management, 83, 38-48.
  • 13.Salzberg, S., 1994. C4.5: Programs for Machine Learning, Machine Learning, Kluwer Academic Publishers, 16, 235-240.
  • 14.Uhlmann, E., Hohwieler, E., Geisert, C., 2017. Intelligent production systems in the era of industrie 4.0 - changing mindsets and business models, Journal of Machine Engineering, 17(2), 5-24.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-55a38b4e-ef6a-4fdb-ad25-f71329741383
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