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Rainfall-runoff forecasting utilizing genetic programming technique

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 analy...

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Main Authors: Ahmed A.N., Hayder G., Rahman R.A.B.A., Borhana A.A.
Other Authors: 57214837520
Format: Article
Published: IAEME Publication 2023
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spelling my.uniten.dspace-250352023-05-29T15:30:46Z Rainfall-runoff forecasting utilizing genetic programming technique Ahmed A.N. Hayder G. Rahman R.A.B.A. Borhana A.A. 57214837520 56239664100 57205651379 55212152300 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. Final 2023-05-29T07:30:46Z 2023-05-29T07:30:46Z 2019 Article 2-s2.0-85060928940 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060928940&partnerID=40&md5=fc57e4d103c43b26a882d93d5d621a62 https://irepository.uniten.edu.my/handle/123456789/25035 10 1 1523 1534 IAEME Publication Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description 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.
author2 57214837520
author_facet 57214837520
Ahmed A.N.
Hayder G.
Rahman R.A.B.A.
Borhana A.A.
format Article
author Ahmed A.N.
Hayder G.
Rahman R.A.B.A.
Borhana A.A.
spellingShingle Ahmed A.N.
Hayder G.
Rahman R.A.B.A.
Borhana A.A.
Rainfall-runoff forecasting utilizing genetic programming technique
author_sort Ahmed A.N.
title Rainfall-runoff forecasting utilizing genetic programming technique
title_short Rainfall-runoff forecasting utilizing genetic programming technique
title_full Rainfall-runoff forecasting utilizing genetic programming technique
title_fullStr Rainfall-runoff forecasting utilizing genetic programming technique
title_full_unstemmed Rainfall-runoff forecasting utilizing genetic programming technique
title_sort rainfall-runoff forecasting utilizing genetic programming technique
publisher IAEME Publication
publishDate 2023
_version_ 1806428501541126144
score 13.222552

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