Data Mining-Based Intelligent Equipment Maintenance System in Telecommunication Network

• Autorzy: Sodiya A. S. , Longe H. O. D. , Ibrahim S. A.
• Języki publikacji: EN

Abstrakty

EN

The concept of data mining, which has become a promising field because of its applications in various fields, is used in this work for strategic equipment maintenance in telecommunication network. Efficient maintenance of equipment in large telecommunication networks is difficult and complex. Thus, there is need for intelligent systems to guide engineers in proper maintenance of equipment in telecommunication network installations. The idea is to apply modified Apriori frequent pattern algorithm to mine frequent faulty events and identity association rules among items in telecommunication network alarm database. We implemented the novel approach on faulty events database of a GSM company in Nigeria. The result shows a promising tool that is much needed for intelligent decision-making in equipment maintenance in telecommunication installations.

Słowa kluczowe

EN

artificial intelligence; deduction; induction; predicate logic; resolution; theorem proving

• Wydawca: Wydawnictwo Politechniki Łódzkiej
• Czasopismo: Journal of Applied Computer Science
• Rocznik: 2005
• Tom: Vol. 13, nr 2
• Strony: 29--38
• Opis fizyczny: Bibliogr. 9 poz.

Twórcy

autor

Sodiya A. S.

• University of Agriculture, Department of Mathematical Sciences, Abeokuta, Nigeria

autor

Longe H. O. D.

• University of Lagos, Computer Science, Lagos, Nigeria

autor

Ibrahim S. A.

• University of Agriculture, Department of Mathematical Sciences, Abeokuta, Nigeria

Bibliografia

• [1] Agrawal & Srikant (1996).
• [2] Gawrysiak, P. and Okoniewski M.: Applying Data Mining Methods for Cellular Radio Network Planning. International Conference on Information Systems, (US' 2000), 2000.
• [3] Han, J., Pei, J. & Yin Y.: Mining Frequent Patterns Without Candidate generation. Proceedings 2000 ACM-SIGMOD International Conference on Management of Data (SIGMOD '00), 2000.
• [4] Karaghoca A. and Kaykayoglu CR.: Strategic data mining by neural networks in the telecommunication sector. International XII. Turcish symposium on Artificial intelligence and Neural Networks -TAINN 2003, 2003.
• [5] Katker S. and Geihs K.: A generic model for fault isolation and event correlation for integrated fault management, Journal of Network and Systems Management, vol. 5, no 2, 1997.
• [6] Katzela I. and Schwarz M.: Schemes for fault indentification in telecommunication networks, IEEE Transactions on Networking, vol. 3, no 6, 1995.
• [7] Klemettinen M., Mannila H., Ronkainen P., Toivonen H. and Verkamo A.: Finding interesting rules from large sets of discovered association rules. In proceedings of the Third International Conference on Information and Knowledge Management (CIKM' 96), Pages 401-407, New York, 1996.
• [8] Sasisekharan R., Seshadri V. and Weiss M.: Data mining and forecasting in large scale telecommunication networks, IEEE Journal, vol. 11, no 1, 1996.
• [9] Steinder M. and Sethi A.S.: The present and future of event correlation: A need for end-to-end service fault localization, Technical Report, CIS Department, University of Delaware, Newark, DE, 2001.