Environmental Modelling through Chaotic Approach for Malaysian West Coast Sea Level.

Abstract

Sea level forecasting is an essential task for coastal engineering, geodetic application, navigation, and recreational activities. Predicting the behavior of future sea level is important for monitoring and forecasting of changes in fishery and marine ecosystems as well as for protection of coastal. This research is focused on the analysis and prediction of hourly sea level time series data at the benchmark station located in Penang by using chaotic approach. The purpose of this research was to identify the presence of chaotic behavior by the phase space reconstruction and Cao methods, and also a local linear approximation method is applied for prediction purposes. The results notified that the value of correlation coefficient between the observed and predicted time series is 0.8838 which is near to one. This reveals that the local linear approximation method can be used to predict the sea level time series in Malaysia. Certainly, the result of this research is expected to help stakeholder such as Department of Survey and Mapping Malaysia (JUPEM) in having a better sea level management.

Water Level Prediction Using Different Numbers of Time Series Data Based on Chaos Approach

“…This chaos approach is an important discovery for predicting phenomena in scientific research. The application of chaos approach is widely used in many types of time series data such as river flow [3], ozone [9] and sea level [4]. Nowadays, the research in the application of this method on water level time series data is growing and being conducted in several countries such as in China [10], Iran [21] and Malaysia [16].…”