Synoptic Maps Forecast Using Spatio-temporal Models

机译：使用时空模型的天气地图预测

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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.

机译：本文的目的是研究几种预报气象摘要地图随时间变化的方法，这些气象摘要地图以可视形式携带信息而没有物体。使用基于窗口的描述符以实现连续性，因此可以进行预测任务。线性和非线性模型用于预测任务，第一个模型基于时空自回归（STAR）模型，而第二个模型则基于人工神经网络。讨论了该方法和获得的结果。

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来源
《International Conference on Computer Aided Systems Theory(EUROCAST 2007); 20070212-16; Las Palmas de Gran Canaria(ES)》|2007年|P.50-56|共7页
会议地点 Las Palmas de Gran Canaria(ES)
作者
J.L. Crespo; P. Bernardos; M.E. Zorrilla; E. Mora;
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作者单位

Department of Applied Mathematics and Computer Sciences, University of Cantabria. Avda. de los Castros s 39005 Santander, Spain;

Department of Mathematics, Statistics and Computation, University of Cantabria. Avda. de los Castros s 39005 Santander, S;

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正文语种 eng
中图分类机器辅助技术;
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Synoptic Maps Forecast Using Spatio-temporal Models

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