Deep convolutional long short-term memory for forecasting wind speed and direction

Deep convolutional long short-term memory for forecasting wind speed and direction

This paper proposed deep learning to create an accurate forecasting system that uses a deep convolutional long short-term memory (DCLSTM) for forecasting wind speed and direction. In order to use the DCLSTM system, wind speed and direction are represented as an image in 2D coordinates and make it to...

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Bibliographic Details
Main Authors:	Anggraini Puspita Sari, Hiroshi Suzuki, Takahiro Kitajima, Takashi Yasuno, Dwi Arman Prasetya, Abd. Rabi'
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2021-06-01
Series:	SICE Journal of Control, Measurement, and System Integration
Subjects:	forecasting wind power lstm clstm machine learning
Online Access:	http://dx.doi.org/10.1080/18824889.2021.1894878

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