Articles | Volume 15, issue 3
https://doi.org/10.5194/hess-15-841-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-15-841-2011
© Author(s) 2011. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
11 Mar 2011
Research article |
| 11 Mar 2011
Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam
A. El-Shafie
Senior Lecturer, Civil and Structural Engineering Dept. University Kebangsaan Malaysia, Malaysia
A. Noureldin
Associate Professor, Electrical and Computer Engineering, Royal Military College, Kingston, Canada
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- Developing reservoir evaporation predictive model for successful dam management M. Allawi et al. https://doi.org/10.1007/s00477-020-01918-6
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- Optimizing Photodegradation Rate Prediction of Organic Contaminants: Models with Fine-Tuned Hyperparameters and SHAP Feature Analysis for Informed Decision Making R. Schossler et al. https://doi.org/10.1021/acsestwater.3c00435
- Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS N. Djurovic et al. https://doi.org/10.1155/2015/742138
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- On the need of ensemble flood forecast in India J. Nanditha & V. Mishra https://doi.org/10.1016/j.wasec.2021.100086
- An Adaptive Intrusion Detection System in the Internet of Medical Things Using Fuzzy-Based Learning M. Alalhareth & S. Hong https://doi.org/10.3390/s23229247
- Adjusting wavelet-based multiresolution analysis boundary conditions for long-term streamflow forecasting I. Maslova et al. https://doi.org/10.1002/hyp.10564
- Bayesian model averaging for the prediction of water main failure for small to large Canadian municipalities G. Kabir et al. https://doi.org/10.1139/cjce-2015-0374
- Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region M. Allawi et al. https://doi.org/10.1007/s00704-017-2292-5
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- An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions H. Chu et al. https://doi.org/10.1016/j.envsoft.2019.104587
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- Application of static and dynamic artificial neural networks for forecasting inflow discharges, case study: Sefidroud Dam reservoir P. Hadiyan et al. https://doi.org/10.1016/j.suscom.2020.100401
- Multistep-ahead daily inflow forecasting using the ERA-Interim reanalysis data set based on gradient-boosting regression trees S. Liao et al. https://doi.org/10.5194/hess-24-2343-2020
- Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue M. Najafzadeh & S. Anvari https://doi.org/10.1007/s11356-023-28236-y
- Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting C. Li et al. https://doi.org/10.1007/s11269-016-1474-8
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- Application of artificial intelligence in geotechnical engineering: A state-of-the-art review A. Baghbani et al. https://doi.org/10.1016/j.earscirev.2022.103991
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- Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models M. Allawi et al. https://doi.org/10.1007/s11356-018-1867-8
- ANNs and inflow forecast to aid stochastic optimization of reservoir operation K. Silva Santos et al. https://doi.org/10.1080/23249676.2019.1687017
- Development of a novel modeling framework based on weighted kernel extreme learning machine and ridge regression for streamflow forecasting A. Samadi-Koucheksaraee & X. Chu https://doi.org/10.1038/s41598-024-81779-z
- Prediction of particulate matter concentration profile in an opencast copper mine in India using an artificial neural network model A. Patra et al. https://doi.org/10.1007/s11869-015-0369-9
28 citations as recorded by crossref.
- Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network P. Kumar et al. https://doi.org/10.1080/19942060.2021.1990134
- Review on generating optimal operation for dam and reservoir water system: simulation models and optimization algorithms S. Saab et al. https://doi.org/10.1007/s13201-022-01593-8
- Monthly inflow forecasting utilizing advanced artificial intelligence methods: a case study of Haditha Dam in Iraq M. Allawi et al. https://doi.org/10.1007/s00477-021-02052-7
- Developing reservoir evaporation predictive model for successful dam management M. Allawi et al. https://doi.org/10.1007/s00477-020-01918-6
- A toy model for monthly river flow forecasting X. Zeng et al. https://doi.org/10.1016/j.jhydrol.2012.05.053
- Optimizing Photodegradation Rate Prediction of Organic Contaminants: Models with Fine-Tuned Hyperparameters and SHAP Feature Analysis for Informed Decision Making R. Schossler et al. https://doi.org/10.1021/acsestwater.3c00435
- Comparison of Groundwater Level Models Based on Artificial Neural Networks and ANFIS N. Djurovic et al. https://doi.org/10.1155/2015/742138
- Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow A. Osman et al. https://doi.org/10.1016/j.jhydrol.2020.124896
- On the need of ensemble flood forecast in India J. Nanditha & V. Mishra https://doi.org/10.1016/j.wasec.2021.100086
- An Adaptive Intrusion Detection System in the Internet of Medical Things Using Fuzzy-Based Learning M. Alalhareth & S. Hong https://doi.org/10.3390/s23229247
- Adjusting wavelet-based multiresolution analysis boundary conditions for long-term streamflow forecasting I. Maslova et al. https://doi.org/10.1002/hyp.10564
- Bayesian model averaging for the prediction of water main failure for small to large Canadian municipalities G. Kabir et al. https://doi.org/10.1139/cjce-2015-0374
- Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region M. Allawi et al. https://doi.org/10.1007/s00704-017-2292-5
- Analyzing the association between the hydrodynamics and bank erosion along the Padma River: 2020 monsoon floods A. Aishi & A. Fahim https://doi.org/10.1080/19475705.2024.2399668
- An ANN-based emulation modelling framework for flood inundation modelling: Application, challenges and future directions H. Chu et al. https://doi.org/10.1016/j.envsoft.2019.104587
- Particulate pollution status and its characteristics during 2015–2016 in Hunan, China C. Dai et al. https://doi.org/10.1016/j.apr.2018.12.001
- Application of static and dynamic artificial neural networks for forecasting inflow discharges, case study: Sefidroud Dam reservoir P. Hadiyan et al. https://doi.org/10.1016/j.suscom.2020.100401
- Multistep-ahead daily inflow forecasting using the ERA-Interim reanalysis data set based on gradient-boosting regression trees S. Liao et al. https://doi.org/10.5194/hess-24-2343-2020
- Long-lead streamflow forecasting using computational intelligence methods while considering uncertainty issue M. Najafzadeh & S. Anvari https://doi.org/10.1007/s11356-023-28236-y
- Deep Feature Learning Architectures for Daily Reservoir Inflow Forecasting C. Li et al. https://doi.org/10.1007/s11269-016-1474-8
- Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia A. El-Shafie et al. https://doi.org/10.5194/hess-16-1151-2012
- Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review F. Fahimi et al. https://doi.org/10.1007/s00704-016-1735-8
- Application of artificial intelligence in geotechnical engineering: A state-of-the-art review A. Baghbani et al. https://doi.org/10.1016/j.earscirev.2022.103991
- Coastal forecast through coupling of Artificial Intelligence and hydro-morphodynamical modelling P. Kumar & N. Leonardi https://doi.org/10.1080/21664250.2023.2233724
- Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models M. Allawi et al. https://doi.org/10.1007/s11356-018-1867-8
- ANNs and inflow forecast to aid stochastic optimization of reservoir operation K. Silva Santos et al. https://doi.org/10.1080/23249676.2019.1687017
- Development of a novel modeling framework based on weighted kernel extreme learning machine and ridge regression for streamflow forecasting A. Samadi-Koucheksaraee & X. Chu https://doi.org/10.1038/s41598-024-81779-z
- Prediction of particulate matter concentration profile in an opencast copper mine in India using an artificial neural network model A. Patra et al. https://doi.org/10.1007/s11869-015-0369-9
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