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Modelling wind speed data in Pulau Langkawi with functional relationship
Nur Ain Al-Hameefatul Jamaliyatul1, Basri Badyalina2, Nurkhairany Amyra Mokhtar3, Adzhar Rambli4, Yong Zulina Zubairi5, Adilah Abdul Ghapor6.
Wind speed influenced weather predictions, aerospace operations, and maritime operations, construction projects. This research aims to examine the relationship between Pulau Langkawi wind speed data during the southwest monsoons in 2019 and 2020. To model wind speed data that follows a normal distribution. An error-in-variables model (EIVM) is utilised, which is a linear functional relationship model (LFRM). The QQ-plots will be utilised to investigate the adequacy of the model’s fit. The maximum likelihood estimation (MLE) approach is employed to estimate the parameters of the model, while the covariance is calculated using the Fisher Information matrix. As a result, it is found that the estimated values demonstrate consistency and reduced dispersion. Thus, the findings could lead to a better knowledge of wind energy prediction.
Affiliation:
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
- Universiti Teknologi MARA, Malaysia
- University of Malaya, Malaysia
- University of Malaya, Malaysia
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Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
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6 |
Immediacy Index
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0.000 |
Rank |
0 |
Indexed by |
Web of Science (SCIE - Science Citation Index Expanded) |
Impact Factor
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JCR (1.009) |
Rank |
Q4 (Multidisciplinary Sciences) |
Additional Information |
JCI (0.15) |
Indexed by |
Scopus 2020 |
Impact Factor
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CiteScore (1.4) |
Rank |
Q2 (Multidisciplinary) |
Additional Information |
SJR (0.251) |
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