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Short-Time Wind Speed Forecast Using Artificial Learning-Based Algorithms
Joint Authors
Ibrahim, Mariam
Alsheikh, Ahmad
Al-Hindawi, Qays
Al-Dahidi, Sameer
ElMoaqet, Hisham
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-25
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
The need for an efficient power source for operating the modern industry has been rapidly increasing in the past years.
Therefore, the latest renewable power sources are difficult to be predicted.
The generated power is highly dependent on fluctuated factors (such as wind bearing, pressure, wind speed, and humidity of surrounding atmosphere).
Thus, accurate forecasting methods are of paramount importance to be developed and employed in practice.
In this paper, a case study of a wind harvesting farm is investigated in terms of wind speed collected data.
For data like the wind speed that are hard to be predicted, a well built and tested forecasting algorithm must be provided.
To accomplish this goal, four neural network-based algorithms: artificial neural network (ANN), convolutional neural network (CNN), long short-term memory (LSTM), and a hybrid model convolutional LSTM (ConvLSTM) that combines LSTM with CNN, and one support vector machine (SVM) model are investigated, evaluated, and compared using different statistical and time indicators to assure that the final model meets the goal that is built for.
Results show that even though SVM delivered the most accurate predictions, ConvLSTM was chosen due to its less computational efforts as well as high prediction accuracy.
American Psychological Association (APA)
Ibrahim, Mariam& Alsheikh, Ahmad& Al-Hindawi, Qays& Al-Dahidi, Sameer& ElMoaqet, Hisham. 2020. Short-Time Wind Speed Forecast Using Artificial Learning-Based Algorithms. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1138837
Modern Language Association (MLA)
Ibrahim, Mariam…[et al.]. Short-Time Wind Speed Forecast Using Artificial Learning-Based Algorithms. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1138837
American Medical Association (AMA)
Ibrahim, Mariam& Alsheikh, Ahmad& Al-Hindawi, Qays& Al-Dahidi, Sameer& ElMoaqet, Hisham. Short-Time Wind Speed Forecast Using Artificial Learning-Based Algorithms. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1138837
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1138837