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A Wind Speed Forecasting Model Based on Artificial Neural Network and Meteorological Data

机译:一种基于人工神经网络和气象数据的风速预测模型

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This paper presents a method for the medium-long-term wind speed prediction based on spatiotemporal evolution of weather fronts and Multi-Layer Perceptron Neural Network (MLP NN) data mining model. The proposed wind speed prediction model is achieved by using historical and current meteorological data, such as pressure, temperature and wind intensity, describing the evolution of the weather fronts in a wide area around the point of interest. This model, trained and tested using real weather data, predicts the 24-h ahead wind speed. The forecasting effectiveness is evaluated comparing the wind forecasted with real data registered in the test site.
机译:本文提出了一种基于天气前沿的时空演变和多层的感知性神经网络(MLP NN)数据挖掘模型的中长期风速预测方法。通过使用历史和当前的气象数据,例如压力,温度和风强度,描述了兴趣点周围的广域出现的变化来实现所提出的风速预测模型。使用真实天气数据培训和测试此模型,预测了24-H前进风速。评估预测有效性,将风量与在测试站点中注册的真实数据进行比较。

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