A Pilot Study Using Chaos Theory to Predict Temperature Time Series in Malaysian Semi Urban Area

Abstract

Chaos theory draws more attention since it has been widely used in modeling various time series. Changes in temperature can cause bad effect on health and lead to death. Therefore, in this study, chaos theory was applied to the temperature time series. The temperature time series is observed hourly in one of Malaysiansemi urban area namely Tanjong Malim,located in the state of Perak. This pilot study begins by detecting the chaos nature in time series through phase space approach and Cao method. Next, the time series was predicted through the local approximation method, a method based on chaos theory. This study resulted that the nature of the observed temperature time series was chaos. Prediction through the local approximation method was success with correlation coefficient value 0.9138. This shows that there exist a strong relationship between the predicted and observed temperature time series. Therefore, chaos theorywas a good approach that can be used to determine the nature and predict temperature time series in the semi urban area. In implication, this findingwas expected to serve stakeholders such as Ministry of Higher Education, Meteorological Department as well as Department of Environment in temperature time series management.