Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load
This paper presents the use of two artificial neural networks models, namely the multilayer feedforward neural network (MLFF) and the recurrent neural network (RNN) are applied for Malaysia’s load forecasting. For this purpose, a half hourly load data is divided equally into three distinct sets for...
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Taru Publications
2010
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my.utm.259362018-03-22T10:53:42Z http://eprints.utm.my/id/eprint/25936/ Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load Mohamed, Norizan Ahmad, Maizah Hura Ismail, Zuhaimy Arshad, Khairil Anuar Q Science (General) This paper presents the use of two artificial neural networks models, namely the multilayer feedforward neural network (MLFF) and the recurrent neural network (RNN) are applied for Malaysia’s load forecasting. For this purpose, a half hourly load data is divided equally into three distinct sets for training, validation and testing. We use backpropagation as the learning algorithm and the sigmoid function as the transfer function for both hidden land output layers. The forecasting performances of were compared between these two models. We use the sum squared error (SSE) as the measure of performance and the correlation coefficient r , as the measure of relationship between the actual and the predicted values. Results show that, multilayer feedforward neural network (MLFF) and recurrent neural network (RNN) have comparable accuracy but the sum squared error for multilayer feedforward neural network (MLFF) is lower, thus making it better model than recurrent neural network (RNN). Taru Publications 2010 Article PeerReviewed Mohamed, Norizan and Ahmad, Maizah Hura and Ismail, Zuhaimy and Arshad, Khairil Anuar (2010) Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load. Journal of Interdisciplinary Mathematics, 13 (2). pp. 125-134. ISSN 0972-0502 https://www.researchgate.net/publication/261657532_Comparing_forecasting_performances_between_multilayer_feedforward_neural_network_and_recurrent_neural_network_in_Malaysia%27s_load |
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Q Science (General) Mohamed, Norizan Ahmad, Maizah Hura Ismail, Zuhaimy Arshad, Khairil Anuar Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
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This paper presents the use of two artificial neural networks models, namely the multilayer feedforward neural network (MLFF) and the recurrent neural network (RNN) are applied for Malaysia’s load forecasting. For this purpose, a half hourly load data is divided equally into three distinct sets for training, validation and testing. We use backpropagation as the learning algorithm and the sigmoid function as the transfer function for both hidden land output layers. The forecasting performances of were compared between these two models. We use the sum squared error (SSE) as the measure of performance and the correlation coefficient r , as the measure of relationship between the actual and the predicted values. Results show that, multilayer feedforward neural network (MLFF) and recurrent neural network (RNN) have comparable accuracy but the sum squared error for multilayer feedforward neural network (MLFF) is lower, thus making it better model than recurrent neural network (RNN). |
| format |
Article |
| author |
Mohamed, Norizan Ahmad, Maizah Hura Ismail, Zuhaimy Arshad, Khairil Anuar |
| author_facet |
Mohamed, Norizan Ahmad, Maizah Hura Ismail, Zuhaimy Arshad, Khairil Anuar |
| author_sort |
Mohamed, Norizan |
| title |
Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
| title_short |
Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
| title_full |
Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
| title_fullStr |
Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
| title_full_unstemmed |
Comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in Malaysia's load |
| title_sort |
comparing forecasting performances between multilayer feedforward neural network and recurrent neural network in malaysia's load |
| publisher |
Taru Publications |
| publishDate |
2010 |
| url |
http://eprints.utm.my/id/eprint/25936/ https://www.researchgate.net/publication/261657532_Comparing_forecasting_performances_between_multilayer_feedforward_neural_network_and_recurrent_neural_network_in_Malaysia%27s_load |
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1643647631999631360 |
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13.211869 |