A Mathematical modelling through chaotic approach to forecast the sea level in Penang

Abstract

Forecasting of sea level is significant since a rising sea level can cause erosion, flood, and inundation. Prediction of the behaviour of a future sea level is crucial for coastal engineering, geodetic applications, navigation, coastal ecosystems, and recreational activities along with observation and prediction of the changes in fisheries and marine environments also coastal fortifications. The data examined is a time series of sea levels recorded hourly in a high-risk area at Penang tidal gauge station. The chaotic approach technique was used to analyze the observed time series data which was divided into two steps: phase space reconstruction and prediction. The purpose of the study comprises to discover the existence of chaotic nature through the phase space reconstruction process and the Cao method. A local linear approach has been used for prediction purposes. The findings indicated that the coefficient of correlation value among the data observed and data predicted was .9356. The result implies the Malaysian sea level of time series can be predicted using the local linear approximation method. These findings are anticipated to support agencies in particular the Department of Survey and Mapping Malaysia (JUPEM) to organize improved management of the sea level.