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Influence of Air Quality Towards The Extreme Rainfall Events: Rough Set Theory

Influence of Air Quality Towards The Extreme Rainfall Events: Rough Set Theory

Authors                   : Payus, C.M., Norela, S. & Azuraliza, A.A

Publication Date     : 2012

Journal                    : Engineering Research and Applications, 544-550

Volume                    : 2

Issue                        : 4

Pages                       : 544-550

Abstract - This research focuses on the development of knowledge model for a prediction of the extreme rainfall events by using the air quality parameters. A knowledge model is a model containing a set of knowledge by rules that was obtained from mining certain amount of data. These rules will help in detection of extreme weather changes events and therefore is significant for safety action plans and mitigations measures, in terms of adaptation to the climate change. In this study, an intelligent approach in data mining called a rough set technique has been used based on its capability on handling uncertain data base that often occurs in the real world problem. As a result, an association and sequential rules were produced and used for prediction of the extreme rainfall events in Petaling Jaya as a case study. Petaling Jaya is an urban and industrialized city in tropical climate of Malaysia which always experiencing flash floods and severe storms that might due to air pollution. A total of 2102 data were obtained from Malaysian Meteorological Department and Department of Environment Malaysia. There were 7 attributes used as input and one attribute as an output for the intelligent systems. Data has been through a pre-processing stage to facilitate the requirement of the modeling process. A total of ten experiments using ten sets of different data have been conducted. The best model was selected from the total models generated from the experiment. As for conclusion, the model has given a promising result with 100% accuracy and the rules obtained have contributing to knowledge for the extreme rainfall events.