Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO
Precise streamflow forecasting is crucial when designing water resource planning and management, predicting flooding, and reducing flood threats. This study invented a novel approach for the monthly water streamflow of the Tigris River in Amarah City, Iraq, by integrating an artificial neural networ...
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| Format: | Article |
| Language: | English |
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Wasit University
2023-08-01
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| Series: | Wasit Journal of Engineering Sciences |
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| Online Access: | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/407 |
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| _version_ | 1850220377899270144 |
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| author | Baydaa Abdul Kareem Salah L. Zubaidi |
| author_facet | Baydaa Abdul Kareem Salah L. Zubaidi |
| author_sort | Baydaa Abdul Kareem |
| collection | DOAJ |
| description | Precise streamflow forecasting is crucial when designing water resource planning and management, predicting flooding, and reducing flood threats. This study invented a novel approach for the monthly water streamflow of the Tigris River in Amarah City, Iraq, by integrating an artificial neural network (ANN) with the particle swarm optimisation algorithm (PSO), depending on data preprocessing. Historical streamflow data were utilised from (2010 to 2020). The primary conclusions of this study are that data preprocessing enhances data quality and identifies the optimal predictor scenario. In addition, it was revealed that the PSO algorithm effectively forecasts the parameters of the suggested model. Also, the outcomes indicated that the suggested approach successfully simulated the streamflow according to multiple statistical criteria, including R2, RMSE, and MAE.
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| format | Article |
| id | doaj-art-68a7bbbf2f034116936419c0a39072ba |
| institution | OA Journals |
| 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-68a7bbbf2f034116936419c0a39072ba2025-08-20T02:07:05ZengWasit UniversityWasit Journal of Engineering Sciences2305-69322663-19702023-08-0111210.31185/ejuow.Vol11.Iss2.407Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSOBaydaa Abdul Kareem0Salah L. Zubaidi1Maysan University _ Engineering collegeDepartment of Civil Engineering, Wasit UniversityPrecise streamflow forecasting is crucial when designing water resource planning and management, predicting flooding, and reducing flood threats. This study invented a novel approach for the monthly water streamflow of the Tigris River in Amarah City, Iraq, by integrating an artificial neural network (ANN) with the particle swarm optimisation algorithm (PSO), depending on data preprocessing. Historical streamflow data were utilised from (2010 to 2020). The primary conclusions of this study are that data preprocessing enhances data quality and identifies the optimal predictor scenario. In addition, it was revealed that the PSO algorithm effectively forecasts the parameters of the suggested model. Also, the outcomes indicated that the suggested approach successfully simulated the streamflow according to multiple statistical criteria, including R2, RMSE, and MAE. https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/407StreamflowANNSSAPSOAmara |
| spellingShingle | Baydaa Abdul Kareem Salah L. Zubaidi Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO Wasit Journal of Engineering Sciences Streamflow ANN SSA PSO Amara |
| title | Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO |
| title_full | Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO |
| title_fullStr | Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO |
| title_full_unstemmed | Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO |
| title_short | Novel hybrid model to improve the monthly streamflow prediction: Integrating ANN and PSO |
| title_sort | novel hybrid model to improve the monthly streamflow prediction integrating ann and pso |
| topic | Streamflow ANN SSA PSO Amara |
| url | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/407 |
| work_keys_str_mv | AT baydaaabdulkareem novelhybridmodeltoimprovethemonthlystreamflowpredictionintegratingannandpso AT salahlzubaidi novelhybridmodeltoimprovethemonthlystreamflowpredictionintegratingannandpso |