Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning
Abstract Predicting wind speed simultaneously at multiple heights, particularly at 10 and 100 metres (m), presents unique challenges due to diverse influences. At lower altitudes, wind speed is significantly affected by surface factors including roughness, vegetation, and man-made structures, causin...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-02-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-88295-8 |
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| author | Alireza Hakimi Parvin Ghafarian |
| author_facet | Alireza Hakimi Parvin Ghafarian |
| author_sort | Alireza Hakimi |
| collection | DOAJ |
| description | Abstract Predicting wind speed simultaneously at multiple heights, particularly at 10 and 100 metres (m), presents unique challenges due to diverse influences. At lower altitudes, wind speed is significantly affected by surface factors including roughness, vegetation, and man-made structures, causing sharp fluctuations, while at higher altitudes, it is primarily influenced by atmospheric conditions, resulting in smoother flow patterns. Traditional models often require separate systems for each altitude, limiting their efficiency and accuracy. This study introduces the brain emotional learning based on basic and functional memories (BELBFM) model, inspired by adaptive emotional learning mechanisms in the mammalian brain, to predict wind speeds at both altitudes simultaneously. Using ERA5 reanalysis data, BELBFM effectively captures the nonlinear dynamics of wind behavior. Evaluation with data from the Persian Gulf demonstrates BELBFM’s high accuracy, enhancing predictive capabilities for applications in renewable energy and structural engineering. This unified model provides a robust and efficient solution for adaptive wind forecasting. |
| format | Article |
| id | doaj-art-feb3858df49147cb8745e43ddb305b90 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-feb3858df49147cb8745e43ddb305b902025-02-09T12:30:28ZengNature PortfolioScientific Reports2045-23222025-02-0115111510.1038/s41598-025-88295-8Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learningAlireza Hakimi0Parvin Ghafarian1Iranian National Institute for Oceanography and Atmospheric Science (INIOAS)Iranian National Institute for Oceanography and Atmospheric Science (INIOAS)Abstract Predicting wind speed simultaneously at multiple heights, particularly at 10 and 100 metres (m), presents unique challenges due to diverse influences. At lower altitudes, wind speed is significantly affected by surface factors including roughness, vegetation, and man-made structures, causing sharp fluctuations, while at higher altitudes, it is primarily influenced by atmospheric conditions, resulting in smoother flow patterns. Traditional models often require separate systems for each altitude, limiting their efficiency and accuracy. This study introduces the brain emotional learning based on basic and functional memories (BELBFM) model, inspired by adaptive emotional learning mechanisms in the mammalian brain, to predict wind speeds at both altitudes simultaneously. Using ERA5 reanalysis data, BELBFM effectively captures the nonlinear dynamics of wind behavior. Evaluation with data from the Persian Gulf demonstrates BELBFM’s high accuracy, enhancing predictive capabilities for applications in renewable energy and structural engineering. This unified model provides a robust and efficient solution for adaptive wind forecasting.https://doi.org/10.1038/s41598-025-88295-8Wind speed modelingBrain emotional learning modelBasic memoryFunctional memoryMachine learning |
| spellingShingle | Alireza Hakimi Parvin Ghafarian Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning Scientific Reports Wind speed modeling Brain emotional learning model Basic memory Functional memory Machine learning |
| title | Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| title_full | Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| title_fullStr | Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| title_full_unstemmed | Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| title_short | Simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| title_sort | simultaneous prediction of 10m and 100m wind speeds using a model inspired by brain emotional learning |
| topic | Wind speed modeling Brain emotional learning model Basic memory Functional memory Machine learning |
| url | https://doi.org/10.1038/s41598-025-88295-8 |
| work_keys_str_mv | AT alirezahakimi simultaneouspredictionof10mand100mwindspeedsusingamodelinspiredbybrainemotionallearning AT parvinghafarian simultaneouspredictionof10mand100mwindspeedsusingamodelinspiredbybrainemotionallearning |