The Options of Using Data Mining Methods in Process Control

Alena Kopcekova; Michal Kopcek; Pavol Tanuska

doi:10.4028/www.scientific.net/AMM.693.123

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 693The Options of Using Data Mining Methods in...

The Options of Using Data Mining Methods in Process Control

Abstract:

The term business intelligence (BI) represents the tools and systems that play a key role in the strategic planning process of the corporation. These systems allow a company to gather, store, access and analyze corporate data to aid in decision-making. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for a company management. The proposed article is logically divided into more sections, where the stages of basic research in the field of data mining are described gradually. This involves the definition of the technology and the list of main advantages and analytical methods incorporated in online analytical processing. Also some typical applications of above mentioned particular methods are introduced. The focus of this paper is to introduce the options of using the data mining methods on the control systems level within the hierarchical control systems model.

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Periodical:

Applied Mechanics and Materials (Volume 693)

Pages:

123-128

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.693.123

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Online since:

December 2014

Authors:

Alena Kopcekova, Michal Kopcek, Pavol Tanuska

Keywords:

Business Intelligence, Data Mining, Process Control Level

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References

[1] D. Mudrončík, Softvér riadiacich systémov, STU Bratislava, (2000).

Google Scholar

[2] P. Tanuška, Získavanie znalostí z databáz v hierarchickom riadení technologických a výrobných procesov, Tézy k inauguračnej prednáške, (2013).

Google Scholar

[3] J. Jadlovský a kol., Návrh distribuovaného systému riadenia pružnej výrobnej linky, In: International Conference Cybernetics and Informatics , Vyšná Boca, (2010).

Google Scholar

[4] H. Meyer, F. Fuchs, K. Thiel, Manufacturing Execution Systems: Optimal Design, Planning, and Deployment. McGraw-Hill Professional, ISBN: 0071623833, (2009).

Google Scholar

[5] M. Liška, Dobívaní znalostí z databází, Ostrava, (2008).

Google Scholar

[6] O. Dolák, Big data, Nové způsoby zpracování a analýzy velkých objemů dat 2011. http: /www. systemonline. cz/clanky/big-data. htm.

Google Scholar

[7] I. Claverie-Berge, Isabelle, Solutions Big Data IBM 2012. http: /www-05. ibm. com/fr/events/netezzaDM_2012/Solutions_Big_Data. pdf.

Google Scholar

[8] T. Kuzár, Tradičný Business Intelligence vs. Big data. Blog, DWH/BI 2012. http: /robime. it/tradicny-business-intelligence-vs-bigdata/#more-2253.

Google Scholar

[9] R. Vrábeľ, M. Abas, Frequency control of singularly perturbed forced duffing´s oscillator. - registrovaný: Web of Science, Master Journal List, Scopus. In: Journal of dynamical and control systems. - ISSN 1079-2724. - Vol. 17, Iss. 3 , s. 451-467, (2011).

DOI: 10.1007/s10883-011-9125-0

Google Scholar