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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Integrating Cluster Analysis to the ARIMA Model for Forecasting Geosensor Data
verfasst von : Sonja Pravilovic, Annalisa Appice, Donato Malerba
Erschienen in: Foundations of Intelligent Systems
Verlag: Springer International Publishing
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Clustering geosensor data is a problem that has recently attracted a large amount of research. In this paper, we focus on clustering geophysical time series data measured by a geo-sensor network. Clusters are built by accounting for both spatial and temporal information of data. We use clusters to produce globally meaningful information from time series obtained by individual sensors. The cluster information is integrated to the ARIMA model, in order to yield accurate forecasting results. Experiments investigate the trade-off between accuracy and efficiency of the proposed algorithm.