Abstract
This paper presents a process classification model based on time series data segmentation, segment classification to identify micro behaviors and behaviors’ integration to identify the way the process is transforming. This approach has been successfully employed in different engineering domains and tasks such as predicting failures in oil process plant, reconstructing trajectories in air traffic control and identifying interaction scenarios in mobile robotic environment.”
Funded by project CAM MADRINET S-0505/TIC/0255.
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Molina, J.M., Garcia, J., Garcia, A.C.B., Melo, R., Correia, L. (2009). Segmentation and Classification of Time-Series: Real Case Studies. In: Corchado, E., Yin, H. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2009. IDEAL 2009. Lecture Notes in Computer Science, vol 5788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04394-9_91
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DOI: https://doi.org/10.1007/978-3-642-04394-9_91
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