Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China
The Huanggang Reservoir capacity is affected by a variety of factors. In order to accurately understand the Huanggang Reservoir capacity change, we develop a new hydrological prediction model based on the LSTM (Long-Short-Term Memory) method, which is used to predict the capacity of the reservoir. I...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2022/2891029 |
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| author | Bibo Dai Jiangbin Wang Xiao Gu Chunyan Xu Xin Yu Haosheng Zhang Canming Yuan Wen Nie |
| author_facet | Bibo Dai Jiangbin Wang Xiao Gu Chunyan Xu Xin Yu Haosheng Zhang Canming Yuan Wen Nie |
| author_sort | Bibo Dai |
| collection | DOAJ |
| description | The Huanggang Reservoir capacity is affected by a variety of factors. In order to accurately understand the Huanggang Reservoir capacity change, we develop a new hydrological prediction model based on the LSTM (Long-Short-Term Memory) method, which is used to predict the capacity of the reservoir. In this modified model, we choose to input multidimensional factors, two fully connected layers, selecting the optimal number of the hidden neurons, the optimizer, and adding the attention mechanism. The result of using the Developed LSTM and usual LSTM shows that the prediction curve of the Developed LSTM model can fit the true value better than the usual LSTM model, and the mean relative error of the Developed LSTM model decreased by 1.15%-3.82%, comparing with the usual LSTM model. Thus, we realize that the Developed LSTM model can make accurately prediction in some reservoir capacity estimations. |
| format | Article |
| id | doaj-art-618bed4d92cc4f3eac6ffccd00f0d379 |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-618bed4d92cc4f3eac6ffccd00f0d3792025-08-20T03:34:52ZengWileyGeofluids1468-81232022-01-01202210.1155/2022/2891029Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, ChinaBibo Dai0Jiangbin Wang1Xiao Gu2Chunyan Xu3Xin Yu4Haosheng Zhang5Canming Yuan6Wen Nie7School of Resources and Civil EngineeringThe Water Resources Allocation Center of Shanmei Reservoir in QuanzhouSchool of Resources and Environmental EngineeringThe Water Resources Allocation Center of Shanmei Reservoir in QuanzhouQuanzhou Institute of Equipment ManufacturingQuanzhou Institute of Equipment ManufacturingState Key Laboratory of Safety and Health for Metal MinesState Key Laboratory of Safety and Health for Metal MinesThe Huanggang Reservoir capacity is affected by a variety of factors. In order to accurately understand the Huanggang Reservoir capacity change, we develop a new hydrological prediction model based on the LSTM (Long-Short-Term Memory) method, which is used to predict the capacity of the reservoir. In this modified model, we choose to input multidimensional factors, two fully connected layers, selecting the optimal number of the hidden neurons, the optimizer, and adding the attention mechanism. The result of using the Developed LSTM and usual LSTM shows that the prediction curve of the Developed LSTM model can fit the true value better than the usual LSTM model, and the mean relative error of the Developed LSTM model decreased by 1.15%-3.82%, comparing with the usual LSTM model. Thus, we realize that the Developed LSTM model can make accurately prediction in some reservoir capacity estimations.http://dx.doi.org/10.1155/2022/2891029 |
| spellingShingle | Bibo Dai Jiangbin Wang Xiao Gu Chunyan Xu Xin Yu Haosheng Zhang Canming Yuan Wen Nie Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China Geofluids |
| title | Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China |
| title_full | Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China |
| title_fullStr | Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China |
| title_full_unstemmed | Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China |
| title_short | Development of Modified LSTM Model for Reservoir Capacity Prediction in Huanggang Reservoir, Fujian, China |
| title_sort | development of modified lstm model for reservoir capacity prediction in huanggang reservoir fujian china |
| url | http://dx.doi.org/10.1155/2022/2891029 |
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