Hybridisation of artificial neural network with particle swarm optimisation for water level prediction

Accurate water level (WL) prediction is essential for the efficient management of various water resource projects. The creation of a reliable model for WL forecasting is still a difficult task in water resource management. This study applies an artificial neural network (ANN) integrated with the pa...

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Main Authors: Sarah J. Mohammed, Salah L. Zubaidi
Format: Article
Language:English
Published: Wasit University 2023-08-01
Series:Wasit Journal of Engineering Sciences
Subjects:
Online Access:https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/404
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author Sarah J. Mohammed
Salah L. Zubaidi
author_facet Sarah J. Mohammed
Salah L. Zubaidi
author_sort Sarah J. Mohammed
collection DOAJ
description Accurate water level (WL) prediction is essential for the efficient management of various water resource projects. The creation of a reliable model for WL forecasting is still a difficult task in water resource management. This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. Monthly WL and climatic variables from 2011 to 2020, were used to construct and validate the proposed technique. The results showed that singular spectrum analysis (SSA) is a high-performance technique for denoising time series. The PSO-ANN model produces good results coefficient of determination (R2) of 0.85.
format Article
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issn 2305-6932
2663-1970
language English
publishDate 2023-08-01
publisher Wasit University
record_format Article
series Wasit Journal of Engineering Sciences
spelling doaj-art-a4bf3a0589bb4e7d87cc5028e828735e2025-08-20T02:07:05ZengWasit UniversityWasit Journal of Engineering Sciences2305-69322663-19702023-08-0111210.31185/ejuow.Vol11.Iss2.404Hybridisation of artificial neural network with particle swarm optimisation for water level prediction Sarah J. Mohammed0Salah L. Zubaidi1Wasit University- Engineering collegeDepartment of Civil Engineering, Wasit University Accurate water level (WL) prediction is essential for the efficient management of various water resource projects. The creation of a reliable model for WL forecasting is still a difficult task in water resource management. This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. Monthly WL and climatic variables from 2011 to 2020, were used to construct and validate the proposed technique. The results showed that singular spectrum analysis (SSA) is a high-performance technique for denoising time series. The PSO-ANN model produces good results coefficient of determination (R2) of 0.85. https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/404Water level predictionsingular spectrum analysisartificial neural networkPSOAL-Kut City
spellingShingle Sarah J. Mohammed
Salah L. Zubaidi
Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
Wasit Journal of Engineering Sciences
Water level prediction
singular spectrum analysis
artificial neural network
PSO
AL-Kut City
title Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
title_full Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
title_fullStr Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
title_full_unstemmed Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
title_short Hybridisation of artificial neural network with particle swarm optimisation for water level prediction
title_sort hybridisation of artificial neural network with particle swarm optimisation for water level prediction
topic Water level prediction
singular spectrum analysis
artificial neural network
PSO
AL-Kut City
url https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/404
work_keys_str_mv AT sarahjmohammed hybridisationofartificialneuralnetworkwithparticleswarmoptimisationforwaterlevelprediction
AT salahlzubaidi hybridisationofartificialneuralnetworkwithparticleswarmoptimisationforwaterlevelprediction