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Simultaneous modelling of rainfall occurrence and amount using a hierarchical nominal-ordinal support vector classifier

机译:使用分层标称-标准支持向量分类器对降雨的发生和数量进行同时建模

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摘要

In this paper we propose a novel computational system for simultaneous modelling and prediction of rainfall occurrence and amount The proposed system is based on a hierarchical system of nominal-ordinal support vector classifiers, the former focussed on the prediction of the rainfall occurrence, and the latter centered in the expected rainfall amount from a set of three different ordinal classes. In addition to the proposed model, we use a novel set of predictive meteorological variables, which improve the classifiers performance in this problem. We evaluate the proposed system in a real problem of rainfall forecast at Santiago de Compostela airport, Spain, showing that the system is able to obtain an accurate prediction of occurrence and rainfall amount, and we discuss the usefulness of the proposed system as part of the airport weather forecast and warning system, in order to improve airport operations.
机译:在本文中,我们提出了一种新颖的计算系统,用于同时进行降雨和雨量的建模和预测。该系统基于标称-支持向量分类器的分层系统,前者着重于降雨的预测,后者以三个不同序数组中的预期降雨量为中心。除了提出的模型,我们还使用了一套新颖的预测性气象变量,从而改善了该问题中分类器的性能。我们在西班牙圣地亚哥德孔波斯特拉机场的一个实际降雨预报中评估了拟议的系统,表明该系统能够获得准确的降水量和降水量预测,并讨论了拟议系统作为气象预报一部分的有用性。机场天气预报和预警系统,以改善机场运营。

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