Identification of Unexpected Behavior of an Automatic Teller Machine Using Principal Component Analysis Models

Autor:	Lidija Bastina, Darius Dilijonas, Rimvydas Simutis
Rok vydání:	2009
Předmět:	Engineering Identification (information) Service (systems architecture) Software business.industry Real-time computing Principal component analysis Early detection Data mining computer.software_genre business GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) computer
Zdroj:	Business Information Systems Workshops ISBN: 9783642034237 BIS (Workshops)
DOI:	10.1007/978-3-642-03424-4_7
Popis:	Early detection of the unexpected behavior of the automatic teller machine (ATM) is crucial for efficient functioning of ATM networks. Because of the high service costs it is very expensive to employ human operators to supervise all ATMs in an ATM network. This paper proposes an automatic identification procedure based on PCA models to supervise continually the ATM networks. This automatic procedure allows detecting the unexpected behavior of the specific automatic teller machine in an ATM network. The proposed procedure has been tested using simulations studies and real experimental data. The simulation results and the first real tests show the efficiency of the proposed procedure. Currently the proposed identification procedure is being implemented in professional software for supervision and control of ATM networks.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c46f691e67d5e31afb81ec805c5ff436 https://doi.org/10.1007/978-3-642-03424-4_7 Zobrazit plný text záznamu