Flood is a frequent occurrence which has a high calamity impact on human lifestyle, environment and economics. Although, there are various methods in the vast literature to predict rainfall distributions so as to prevent flood occurrences, the accuracy of these methods still remain a huge concern. Therefore, this study explores the application of the fuzzy time series method in order to obtain more accurate rainfall distribution predictions. Data for the study were collected from the Drainage and Irrigation Department Perlis (DID) of Malaysia. The data were analysed and validated using the mean square error (MSE) and the root mean squared error (RMSE). The result of the validation was compared with selected results in previous methods. The validation analysis depicts that this method has a higher forecasting accuracy than the previous methods.

No abstract

Flood is a frequent occurrence which has a high calamity impact on human lifestyle, environment and economics. Although, there are various methods in the vast literature to predict rainfall distributions so as to prevent flood occurrences, the accuracy of these methods still remain a huge concern. Therefore, this study explores the application of the fuzzy time series method in order to obtain more accurate rainfall distribution predictions. Data for the study were collected from the Drainage and Irrigation Department Perlis (DID) of Malaysia. The data were analysed and validated using the mean square error (MSE) and the root mean squared error (RMSE). The result of the validation was compared with selected results in previous methods. The validation analysis depicts that this method has a higher forecasting accuracy than the previous methods.

No abstract