Abstract
The aim of this study is to model the temperature time series at Malaysian high population area during dry season through chaos theory. The selected high population area is Shah Alam located in Selangor state of Malaysia. Chaos theory modelling is categorized into two parts namely analysis and prediction. Analysis by the phase space plot showed that the nature of the observed temperature time series is chaos. Hence, the time series is predicted via the chaotic model. Results from the chaotic model showed that the temperature time series is well predicted with Pearson correlation coefficient near to 1. The result is compared with the traditional method of autoregressive linear model. Based on the computed values of average absolute error, root mean squared error and Pearson correlation coefficient, the chaotic model is found better in predicting temperature time series at Shah Alam area during dry season. This indicates that the chaos theory is applicable for temperature time series at Malaysian high population area. This finding is expected to facilitate stakeholders such as Malaysian Meteorological Department and Department of Environment Malaysia in managing temperature and climate change problem.
Highlights
Recent developments in information technology and computing ability over the last few decades have made it possible for in-depth exploration of complex systems in the natural sciences
Results and Discussion hourly temperature time series at Malaysian high population area, the projection yields a clear attractor in a well-defined region
The existence of attractor suggests that the nature of the studied temperature time is chaos. Since it is confirmed from phase space plot that the nature of the observed temperature time series is chaos, this confirms that the prediction model through chaos theory namely chaotic model can be developed
Summary
Recent developments in information technology and computing ability over the last few decades have made it possible for in-depth exploration of complex systems in the natural sciences. The main issue is to understand the dynamics of the complex systems with disorder structure. The disorder structure needs to be explored before any further action such as the prediction of the complex systems can be done. One of the theory which can be applied is called chaos theory. In modern meteorological and hydrological studies, some complex systems such as river flow, rainfall, air pollution, sea level and temperature need to be modelled in order to understand the structure as well as the nature of the data. Chaos theory is applied in order to model the chosen complex data and study the nature of the data
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