Rainfall-runoff forecasting utilizing genetic programming technique

• Main Authors: Ahmed, A.N., Hayder, G., Rahman, R.A.B.A., Borhana, A.A.
• Format: Article
• Language: English
• Published: 2020
• Online Access: http://dspace.uniten.edu.my/jspui/handle/123456789/13213

This paper reports how the rainfall-runoff is forecasted utilizing Genetic Programming (GP) technique. It is a program that was inspired by biological processes such as mutation, crossover, and inversion in order to create a new generation. It is a program that will learn and improve with each analysis done. It uses a trial an error method in order to forecast rainfall-runoff. GP uses Root Mean Squared Error (RMSE) as an indication of how accurate the results of the forecast. The lower and closer the RMSE to zero, the more accurate the rainfall-runoff forecasted. The study consists of running the data on the software until the lowest RMSE is obtained. This research contains three models which use a different number of input variables to see whether it will give an impact on the rainfall-runoff forecasting. The results are compared and a bar chart is plotted. © IAEME Publication.