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A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia

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...

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Main Authors: Sarkar, Rasel, Julai, Sabariah, Hossain, Sazzad, Chong, Wen Tong, Rahman, Mahmudur
Format: Article
Published: Hindawi 2019
Subjects:
TJ Mechanical engineering and machinery
Online Access:http://eprints.um.edu.my/23521/
https://doi.org/10.1155/2019/6403081
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spelling my.um.eprints.235212020-01-22T01:38:59Z http://eprints.um.edu.my/23521/ A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia Sarkar, Rasel Julai, Sabariah Hossain, Sazzad Chong, Wen Tong Rahman, Mahmudur TJ Mechanical engineering and machinery 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. © 2019 Rasel Sarkar et al. Hindawi 2019 Article PeerReviewed Sarkar, Rasel and Julai, Sabariah and Hossain, Sazzad and Chong, Wen Tong and 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, 2019. pp. 1-14. ISSN 1024-123X https://doi.org/10.1155/2019/6403081 doi:10.1155/2019/6403081
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
Sarkar, Rasel
Julai, Sabariah
Hossain, Sazzad
Chong, Wen Tong
Rahman, Mahmudur
A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
description 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. © 2019 Rasel Sarkar et al.
format Article
author Sarkar, Rasel
Julai, Sabariah
Hossain, Sazzad
Chong, Wen Tong
Rahman, Mahmudur
author_facet Sarkar, Rasel
Julai, Sabariah
Hossain, Sazzad
Chong, Wen Tong
Rahman, Mahmudur
author_sort Sarkar, Rasel
title A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
title_short A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
title_full A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
title_fullStr A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
title_full_unstemmed A Comparative Study of Activation Functions of NAR and NARX Neural Network for Long-Term Wind Speed Forecasting in Malaysia
title_sort comparative study of activation functions of nar and narx neural network for long-term wind speed forecasting in malaysia
publisher Hindawi
publishDate 2019
url http://eprints.um.edu.my/23521/
https://doi.org/10.1155/2019/6403081
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score 13.211869

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