Modelling wind speed data in Pulau Langkawi with functional relationship - Nur Ain Al-Hameefatul Jamaliyatul,; Basri Badyalina,; Nurkhairany Amyra Mokhtar,; Adzhar Rambli,; Yong Zulina Zubairi,; Adilah Abdul Ghapor, (Penerbit Universiti Kebangsaan Malaysia, 2023)
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.