Grid Search of Convolutional Neural Network model in the case of load forecasting
The Convolutional Neural Network (CNN) model is one of the most effective models for load forecasting with hyperparameters which can be used not only to determine the CNN structure and but also to train the CNN model. This paper proposes a framework for Grid Search hyperparameters of the CNN model....
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2021-03-01
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| Series: | Archives of Electrical Engineering |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/118966/PDF/art02.pdf |
| _version_ | 1818172465766989824 |
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| author | Thanh Ngoc Tran |
| author_facet | Thanh Ngoc Tran |
| author_sort | Thanh Ngoc Tran |
| collection | DOAJ |
| description | The Convolutional Neural Network (CNN) model is one of the most effective models for load forecasting with hyperparameters which can be used not only to determine the CNN structure and but also to train the CNN model. This paper proposes a framework for Grid Search hyperparameters of the CNN model. In a training process, the optimal models will specify conditions that satisfy requirement for minimum of accuracy scores of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). In the testing process, these optimal models will be used to evaluate the results along with all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. Load demand data of Queensland (Australia) and Ho Chi Minh City (Vietnam) were utilized to verify the accuracy and reliability of the Grid Search framework. |
| first_indexed | 2024-12-11T19:13:03Z |
| format | Article |
| id | doaj.art-ff7730e5663344188494082023db0030 |
| institution | Directory Open Access Journal |
| issn | 2300-2506 |
| language | English |
| last_indexed | 2024-12-11T19:13:03Z |
| publishDate | 2021-03-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Electrical Engineering |
| spelling | doaj.art-ff7730e5663344188494082023db00302022-12-22T00:53:43ZengPolish Academy of SciencesArchives of Electrical Engineering2300-25062021-03-01vol. 70No 12530https://doi.org/10.24425/aee.2021.136050Grid Search of Convolutional Neural Network model in the case of load forecastingThanh Ngoc Tran0Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, 12 Nguyen Van Bao, Ward 4, Go Vap District, Ho Chi Minh City, VietnamThe Convolutional Neural Network (CNN) model is one of the most effective models for load forecasting with hyperparameters which can be used not only to determine the CNN structure and but also to train the CNN model. This paper proposes a framework for Grid Search hyperparameters of the CNN model. In a training process, the optimal models will specify conditions that satisfy requirement for minimum of accuracy scores of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). In the testing process, these optimal models will be used to evaluate the results along with all other ones. The results indicated that the optimal models have accuracy scores near the minimum values. Load demand data of Queensland (Australia) and Ho Chi Minh City (Vietnam) were utilized to verify the accuracy and reliability of the Grid Search framework.https://journals.pan.pl/Content/118966/PDF/art02.pdfload forecastinggrid searchconvolutional neural network |
| spellingShingle | Thanh Ngoc Tran Grid Search of Convolutional Neural Network model in the case of load forecasting Archives of Electrical Engineering load forecasting grid search convolutional neural network |
| title | Grid Search of Convolutional Neural Network model in the case of load forecasting |
| title_full | Grid Search of Convolutional Neural Network model in the case of load forecasting |
| title_fullStr | Grid Search of Convolutional Neural Network model in the case of load forecasting |
| title_full_unstemmed | Grid Search of Convolutional Neural Network model in the case of load forecasting |
| title_short | Grid Search of Convolutional Neural Network model in the case of load forecasting |
| title_sort | grid search of convolutional neural network model in the case of load forecasting |
| topic | load forecasting grid search convolutional neural network |
| url | https://journals.pan.pl/Content/118966/PDF/art02.pdf |
| work_keys_str_mv | AT thanhngoctran gridsearchofconvolutionalneuralnetworkmodelinthecaseofloadforecasting |