Assessment of Three Learning Machines for Long-Term Prediction of Wind Energy in Palestine
Joint Authors
Khatib, Tamer
Deria, Reziq
Isead, Asma
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
In this research, an approach for predicting wind energy in the long term has been developed.
The aim of this prediction is to generate wind energy profiles for four cities in Palestine based on wind energy profile of another fifth city.
Thus, wind energy data for four cities, namely, Nablus city, are used to develop the model; meanwhile, wind energy data for Hebron, Jenin, Ramallah, and Jericho cities are predicted based on that.
Three machine learning algorithms are used in this research, namely, Cascade-forward neural network, random forests, and support vector machines.
The developed models have two input variables which are daily average cubic wind speed and the standard deviation, while the target is daily wind energy.
The R-squared values for the developed Cascade-forward neural network, random forests, and support vector machines models are found to be 0.9996, 0.9901, and 0.9991, respectively.
Meanwhile, RMSE values for the developed models are found to be 41.1659 kWh, 68.4101 kWh, and 205.10 kWh, respectively.
American Psychological Association (APA)
Khatib, Tamer& Deria, Reziq& Isead, Asma. 2020. Assessment of Three Learning Machines for Long-Term Prediction of Wind Energy in Palestine. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1201017
Modern Language Association (MLA)
Khatib, Tamer…[et al.]. Assessment of Three Learning Machines for Long-Term Prediction of Wind Energy in Palestine. Mathematical Problems in Engineering No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1201017
American Medical Association (AMA)
Khatib, Tamer& Deria, Reziq& Isead, Asma. Assessment of Three Learning Machines for Long-Term Prediction of Wind Energy in Palestine. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1201017
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1201017