Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia
Complex networks; Forecasting; Genetic algorithms; Neural networks; Wind; Wind power; Case-studies; Complex terrains; Malaysia; Malaysians; MCP; Measure-correlate-predict; Model inputs; Spatial modelling; Wind maps; Wind speed models; Surface roughness; alternative energy; artificial neural network;...
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2023
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my.uniten.dspace-268732023-05-29T17:37:26Z Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia Kim Hwang Y. Zamri Ibrahim M. Ismail M. Najah Ahmed A. Albani A. 57317168600 57207778474 57210403363 57214837520 55772882600 Complex networks; Forecasting; Genetic algorithms; Neural networks; Wind; Wind power; Case-studies; Complex terrains; Malaysia; Malaysians; MCP; Measure-correlate-predict; Model inputs; Spatial modelling; Wind maps; Wind speed models; Surface roughness; alternative energy; artificial neural network; genetic algorithm; renewable resource; roughness; wind power; Malaysia This study aimed to create a Malaysian wind map of greater accuracy. Compared to a previous wind map, spatial modeling input was increased. The Genetic Algorithm-optimized Artificial Neural Network Measure�Correlate�Predict method was used to impute missing data, and managed to control over- or under-prediction issues. The established wind map was made more reliable by including surface roughness to simulate wind flow over complex terrain. Validation revealed that the current wind map is 33.833% more accurate than the previous wind map. Furthermore, the correlation coefficient between wind map-simulated data and observed data was high as 0.835. In conclusion, the new and improved wind map for Malaysia simulates data with acceptable accuracy. � The Author(s) 2021. Final 2023-05-29T09:37:26Z 2023-05-29T09:37:26Z 2022 Article 10.1177/0309524X211055836 2-s2.0-85118243117 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118243117&doi=10.1177%2f0309524X211055836&partnerID=40&md5=d111dee6eeb90f8f57d3c29cc9c29e44 https://irepository.uniten.edu.my/handle/123456789/26873 46 3 818 843 SAGE Publications Inc. Scopus |
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Malaysia |
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Complex networks; Forecasting; Genetic algorithms; Neural networks; Wind; Wind power; Case-studies; Complex terrains; Malaysia; Malaysians; MCP; Measure-correlate-predict; Model inputs; Spatial modelling; Wind maps; Wind speed models; Surface roughness; alternative energy; artificial neural network; genetic algorithm; renewable resource; roughness; wind power; Malaysia |
| author2 |
57317168600 |
| author_facet |
57317168600 Kim Hwang Y. Zamri Ibrahim M. Ismail M. Najah Ahmed A. Albani A. |
| format |
Article |
| author |
Kim Hwang Y. Zamri Ibrahim M. Ismail M. Najah Ahmed A. Albani A. |
| spellingShingle |
Kim Hwang Y. Zamri Ibrahim M. Ismail M. Najah Ahmed A. Albani A. Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| author_sort |
Kim Hwang Y. |
| title |
Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| title_short |
Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| title_full |
Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| title_fullStr |
Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| title_full_unstemmed |
Wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: A case study of Malaysia |
| title_sort |
wind speed modeling over complex terrain with the artificial neural network in the measure-correlate-predict technique: a case study of malaysia |
| publisher |
SAGE Publications Inc. |
| publishDate |
2023 |
| _version_ |
1806427987144343552 |
| score |
13.211869 |