Rainfall-runoff forecasting utilizing genetic programming technique

Ali N. Ahmed, Gasim Hayder Ahmed Salih, Raihana Aliya Binti Abdul Rahman, Abdoulhdi A. Borhana

Research output: Contribution to journalArticle

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)1523-1534
Number of pages12
JournalInternational Journal of Civil Engineering and Technology
Issue number1
Publication statusPublished - Jan 2019

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Rainfall-runoff forecasting utilizing genetic programming technique'. Together they form a unique fingerprint.

  • Cite this