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Anomaly monitoring framework based on intelligent data analysis. (2013)
Conference Proceeding
RATTADILOK, P., PETROVSKI, A. and PETROVSKI, S. 2013. Anomaly monitoring framework based on intelligent data analysis. In Yin, H., Tang, K., Gao, Y., Klawonn, F., Lee, M., Weise, T., Li, B. and Yao, X. (eds.) Proceedings of the 14th International conference on intelligent data engineering and automated learning (IDEAL 2013), 20-23 October 2013, Hefei, China. Lecture notes in computer science, 8206. Berlin: Springer [online], pages 134-141. Available from: https://doi.org/10.1007/978-3-642-41278-3_17

Real-time data processing has become an increasingly important challenge as the need for faster analysis of big data widely manifests itself. In this research, several methods of Computational Intelligence have been applied for identifying possible a... Read More about Anomaly monitoring framework based on intelligent data analysis..

Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. (2013)
Conference Proceeding
RATTADILOK, P. and PETROVSKI, A. 2013. Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning. In Proceedings of the 2013 IEEE international conference on computational intelligence and virtual environments for measurement systems and applications (CIVEMSA 2013), 15-17 July 2013, Milan, Italy. New York: IEEE [online], article number 6617402, pages 93-98. Available from: https://doi.org/10.1109/CIVEMSA.2013.6617402

The paper proposes a generic approach to building inferential measurement systems. The large amount of data needed to be acquired and processed by such systems necessitates the use of machine learning techniques. In this study, an inferential measure... Read More about Inferential measurements for situation awareness: enhancing traffic surveillance by machine learning..