Abstract:
Predicting the sea water level is very important as an increasing of sea level may lead to
many disaster such as flood, inundation and coastal erosion. This research shows the
application of chaotic approach for Malaysian Borneo (Sabah) sea level. The studied
data, is a time series of observed sea level by hourly at the selected benchmark station
located in the district of Sandakan, Kudat and Kota Kinabalu, Sabah respectively. This
study has two objectives, which is to detect the presence of chaotic dynamics in data and
to predict the data. To achieve the first objective, multidimensional phase space is
reconstructed using the parameters of the delay time and , in Kota Kinabalu
with embedding dimension d = 6 and d = 3. For Kudat, and with embedding
dimension d = 5 and d = 3, and for Sandakan and with embedding
dimension d = 5 and d = 4, were used respectively. Both time delay and embedding
dimension values was derived from the Cao method and Average Mutual Information.
The results from the phase space plot and Cao method will shows that the data are
chaotic or not. To achieve the second objectives, 1 hour ahead forecasting for an hourly
sea level time series is carried out by using the Local Linear Approximation method and
correlation coefficient is used for testing the prediction performance. However, this
method required to use MATLAB for forecast the data. The result shows the correlation
coefficient value between the actual and foretasted data is 0.9 which is near to 1. This
shows the reliability of the local approximation method to forecast the time series of sea
level rise and also shows a positive sign that this chaotic approach is applicable to the
time series of sea level in Malaysia.
