Abstract
Time series mining is a new area of research in temporal data bases. Hitherto various methods have been presented for time series mining which the most of an existing works in different applied areas have been focused on event prediction. Event prediction is one of the main goals of time series mining which can play an effective role for appropriate decision making in different applied areas. Due to the variety and plenty of event prediction methods in time series and lack of a proper context for their systematic introduction, in this paper, a classification is proposed for event prediction methods in time series. Also, event prediction methods in time series are evaluated based on the proposed classification by some proposed measures. Using the proposed classification can be beneficial in selecting the appropriate method and can play an effective role in the analysis of event prediction methods in different application domains.
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Mehrmolaei, S., Keyvanpourr, M.R. (2015). A Brief Survey on Event Prediction Methods in Time Series. In: Silhavy, R., Senkerik, R., Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Artificial Intelligence Perspectives and Applications. Advances in Intelligent Systems and Computing, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-319-18476-0_24
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DOI: https://doi.org/10.1007/978-3-319-18476-0_24
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