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An application of supervised and unsupervised learning approaches to telecommunications fraud detection.

, and . Knowl. Based Syst., 21 (7): 721-726 (2008)

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SCOLS-FuM: A Hybrid Fuzzy Modeling Method for Telecommunications Time-Series Forecasting., and . Informatica, 25 (2): 221-239 (2014)Exploiting Reverse Direction Protocol in Full Duplex WLANs., and . MOCAST, page 1-4. IEEE, (2020)Designing an expert system for fraud detection in private telecommunications networks.. Expert Syst. Appl., 36 (9): 11559-11569 (2009)A TSK-based fuzzy system for telecommunications time-series forecasting., , , and . IEEE Conf. of Intelligent Systems, page 146-151. IEEE, (2012)Forecasting of telecommunications time-series via an Orthogonal Least Squares-based fuzzy model., , , and . FUZZ-IEEE, page 1-8. IEEE, (2012)3D geospatial visualizations: Animation and motion effects on spatial objects., , , , and . Comput. Geosci., (2018)An Application of Decision Trees for Rule Extraction Towards Telecommunications Fraud Detection., and . KES (2), volume 4693 of Lecture Notes in Computer Science, page 1112-1121. Springer, (2007)X-EDCA: A cross-layer MAC-centric mechanism for efficient multimedia transmission in congested IEEE 802.11e infrastructure networks., , , and . IWCMC, page 1724-1730. IEEE, (2011)Sharing transmission opportunity in ad-hoc WLANs supporting VoIP., and . MOCAST, page 1-4. IEEE, (2018)Telecommunications Data Forecasting Based on a Dynamic Neuro-fuzzy Network., and . ISNN (1), volume 6675 of Lecture Notes in Computer Science, page 529-537. Springer, (2011)