APPLICATION OF CHAOTIC APPROACH FOR MALAYSIAN WEST COAST SEA LEVEL

Abstract

Predicting sea water level is important as an increasing of sea level may lead to inundation, flood and coastal erosion. This study is the application of chaotic approach for Malaysian west coast sea level. Studied data is a time series of observed sea level hourly at benchmark station located in the district of Georgetown in Penang and Kukup, Johor respectively. This research has two objectives, which is to detect the presence of chaos in data and to predict it. To achieve objective number 1, multidimensional phase space is reconstructed using the parameters of the delay time and , in Penang with embedding dimension d = 6 and d = 4. For Kukup, and with embedding dimension d = 8 and d = 7 were used respectively. Both time delay and embedding dimension values was derived from the Average Mutual Information (AMI) and Cao method. The results from the phase space diagram and parameter plot of Cao method reveals that the data are chaotic. To achieve objectives number 2, 1 hour ahead forecasting for an hourly sea level time series is carried out using the Local Linear Approximation (LLA) method and compared with the Auto Regressive Linear (ARL) method for testing the prediction performance. However, this method used MATLAB to forecast the data. Correlation coefficient (cc) value between the actual and foretasted data is only 0.88. This shows the reliability of the local approximation method to forecast the time series of sea level and it’s a positive sign that this chaotic approach is applicable to the time series of sea level in Malaysian West Coast.