小波包分解
小波
风速
临近预报
风速计
计算机科学
离散小波变换
人工神经网络
网络数据包
小波变换
人工智能
机器学习
气象学
地理
计算机网络
作者
Pedro Júnior Zucatelli,Erick Giovani Sperandio Nascimento,Alex Álisson Bandeira Santos,Davidson Martins Moreira
标识
DOI:10.1080/15502287.2020.1841335
摘要
This work presents a novel investigation on the nowcasting prediction of wind speed for three sites in Bahia, Brazil. For this, it was applied the computational intelligence by supervised machine learning using different artificial neural network technique, which was trained, validated, and tested using time series are derived from measurements that are acquired in towers equipped with anemometers at heights of 100.0, 120.0 and 150.0 m. To define the most efficient ANN, different topologies were tested using MLP and RNN, applying Wavelet packet decomposition (bior, coif, db, dmey, rbior, sym). The best statistical analysis was RNN + discrete Meyer wavelet.HighlightsA new methodology for improving forecast accuracy of wind speed using artificial neural network (ANN) and Wavelet packet decomposition.Using machine learning and Wavelet packet decomposition to nowcast wind speed (m/s).To predict the wind speed at 100.0 m, 120.0 m and 150.0 m height in tropical region.Performance evaluation of Wavelet packet decomposition applying 48 different mother Wavelet functions.ANN approach for the estimation of nine types of wind speed time series.The proposed hybrid model (ANN + Wavelet packet decomposition) is capable of wind speed forecasting efficiently.
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