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Interpolation of Wind Speed Using the Self-Organizing Maps in Malaysia
Nor Shaziera Binti Mohamad Shah
Supervisor: Assoc. Prof. Ts. Dr. Mohd Zamri Ibrahim
Bachelor of Technology (Environment)
School of Ocean Engineering
Universiti Malaysia Terengganu
The determining the wind speed in a wide area system and high dimensional space is
difficult and supervised learning neural networks that the network need external help.
In this study, its present novel approach to spatial wind speed estimation in Malaysia
by using Self-Organizing Map (SOM) method to obtain a map of the average wind
speed over the entire region in the Malaysia. The mean wind speed for 37 stations is
the main input use in trained SOM. And then estimated wind data measured to test
error and correlation coefficient by using the Pearson’s Correlation Equation and lastly
wind speed at different height are extrapolated by using the power low profile. The
results showed with the map of the average wind speed at different height in Malaysia
with the validation set by the SOM network. The SOM is powerful method for mapping
in large area and able to reduce that maps high dimensional data into smaller
dimensions.
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