Flood forecasting at Jerantut, Pahang by using artificial neural network (ANN)

• Main Author: Nurul Izzah, Osman
• Format: Undergraduates Project Papers
• Language: English
• Published: 2017
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/25620/1/Flood%20forecasting%20at%20Jerantut%2C%20Pahang%20by%20using%20artificial%20neural%20network.pdf; http://umpir.ump.edu.my/id/eprint/25620/

Developing flood forecasting is necessity especially for east coast peninsular Malaysia that experienced flood every year due to northeast monsoon. A strong performance of forecasting model to predict water level could be a solution to minimize bad impact of flood. Artificial Neural Network (ANN) use historical data to find data pattern to make data forecasting. Historical data require to generate the result by forecast a model. A case study had been applied at the Sungai Yap at Pahang River where hourly water level data dated from 1985 until 2015 have been used to forecast hourly water level. In this study, three type of time interval 1, 3 and 6 hour and 5 types of data input which are 3, 4, 5, 6 and 7 were analysed. Result showed that all data input successfully achieve high accuracy forecasting result where 0.9 to 1 for NSC value were recorded.