DISSERTATION TITLE: A FORECASTING MODEL OF AIR POLLUTION INDEX BASED ON MARKOV CHAIN METHOD

Most metropolitan cities and towns in Malaysia are experiencing elevated ground level air pollutants concentration as it had a linked to rapid industrialization and the development of economy. It has become a crucial concerns as it had wide ranging impact from the aspect of public health to national economics. Therefore, it is urgent to forecast and evaluate the air pollutants concentrations for health agencies and local
environmental. Due to this issue, this study proposes a forecasting tool to predict the air quality with Markov chain model. The proposed method introduces the Markov
chain as an operator to evaluate the distribution of the pollution level in the long term. Markov chain is commonly used in stock market analysis, manpower planning and in many other areas because of its efficiency in prediction for the long run behavior.