Abstract
The objective of this paper is to study several approaches to forecasting the temporal evolution of meteorological synoptic maps that carry information in visual form but without objects. Window-based descriptors are used in order to accomplish continuity so the prediction task is possible. Linear and non-linear models are applied for the prediction task, the first one being based on a spatio-temporal autoregressive (STAR) model whereas the second one is based on artificial neural networks. The method and obtained results are discussed.
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Crespo, J.L., Bernardos, P., Zorrilla, M.E., Mora, E. (2007). Synoptic Maps Forecast Using Spatio-temporal Models. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2007. EUROCAST 2007. Lecture Notes in Computer Science, vol 4739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75867-9_7
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DOI: https://doi.org/10.1007/978-3-540-75867-9_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-75866-2
Online ISBN: 978-3-540-75867-9
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