A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
Joint Authors
Chong, W. T.
Sarkar, Rasel
Julai, Sabariah
Hossain, Sazzad
Rahman, Mahmudur
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-28
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Since wind power is directly influenced by wind speed, long-term wind speed forecasting (WSF) plays an important role for wind farm installation.
WSF is essential for controlling, energy management and scheduled wind power generation in wind farm.
The proposed investigation in this paper provides 30-days-ahead WSF.
Nonlinear Autoregressive (NAR) and Nonlinear Autoregressive Exogenous (NARX) Neural Network (NN) with different network settings have been used to facilitate the wind power generation.
The essence of this study is that it compares the effect of activation functions (namely, tansig and logsig) in the performance of time series forecasting since activation function is the core element of any artificial neural network model.
A set of wind speed data was collected from different meteorological stations in Malaysia, situated in Kuala Lumpur, Kuantan, and Melaka.
The proposed activation functions tansig of NARNN and NARXNN resulted in promising outcomes in terms of very small error between actual and predicted wind speed as well as the comparison for the logsig transfer function results.
American Psychological Association (APA)
Sarkar, Rasel& Julai, Sabariah& Hossain, Sazzad& Chong, W. T.& Rahman, Mahmudur. 2019. A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1196545
Modern Language Association (MLA)
Sarkar, Rasel…[et al.]. A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia. Mathematical Problems in Engineering No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1196545
American Medical Association (AMA)
Sarkar, Rasel& Julai, Sabariah& Hossain, Sazzad& Chong, W. T.& Rahman, Mahmudur. A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1196545
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196545