Articles | Volume 13, issue 3
https://doi.org/10.5194/hess-13-411-2009
© Author(s) 2009. 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-13-411-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
19 Mar 2009
Multi-criteria validation of artificial neural network rainfall-runoff modeling
R. Modarres
Faculty of Natural Resources, Isfahan University of Technology, Isfahan, Iran
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Cited
44 citations as recorded by crossref.
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- Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting M. Dehghani et al. 10.1007/s12517-017-2990-4
- Rain gauge network design for flood forecasting using multi-criteria decision analysis and clustering techniques in lower Mahanadi river basin, India A. Kar et al. 10.1016/j.ejrh.2015.07.003
- Monthly discharge forecasting using wavelet neural networks with extreme learning machine B. Li & C. Cheng 10.1007/s11431-014-5712-0
- Improving stream flow estimation by incorporating time delay approach in soft computing models V. Garg et al. 10.1080/09715010.2019.1676171
- Genetic Algorithm Driven ANN Model for Runoff Estimation N. Dhamge et al. 10.1016/j.protcy.2012.10.060
- Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China T. Zhang et al. 10.3390/w10081028
- Artificial Neural Networks for Event Based Rainfall-Runoff Modeling A. Sarkar & R. Kumar 10.4236/jwarp.2012.410105
- A sensitive and efficient method for simultaneous trace detection and identification of triterpene acids and its application to pharmacokinetic study G. Chen et al. 10.1016/j.talanta.2012.06.053
- Comparison of Stabilization Ability of Models for Hydrological Time Series with a Deterministic Trend H. Xie et al. 10.1155/2015/218289
- Monthly evaporation forecasting using artificial neural networks and support vector machines G. Tezel & M. Buyukyildiz 10.1007/s00704-015-1392-3
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- Monthly rainfall–runoff modelling using artificial neural networks F. Machado et al. 10.1080/02626667.2011.559949
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- Multilayer perceptron with different training algorithms for streamflow forecasting P. Hosseinzadeh Talaee 10.1007/s00521-012-1287-5
- Short‐Term Power Generation Energy Forecasting Model for Small Hydropower Stations Using GA‐SVM G. Li et al. 10.1155/2014/381387
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43 citations as recorded by crossref.
- Regional Dry Spells Frequency Analysis by L-Moment and Multivariate Analysis R. Modarres 10.1007/s11269-009-9556-5
- Projected streamflow in the Huaihe River Basin (2010–2100) using artificial neural network C. Gao et al. 10.1007/s00477-009-0355-6
- Successive-station monthly streamflow prediction using neuro-wavelet technique A. Danandeh Mehr et al. 10.1007/s12145-013-0141-3
- Association Between Immediacy of Citations and Altmetrics in COVID-19 Research by Artificial Neural Networks N. Ran 10.1017/dmp.2021.277
- Monthly stream flow forecasting via dynamic spatio-temporal models M. Dehghani et al. 10.1007/s00477-014-0967-3
- Generalized autoregressive conditional heteroscedasticity modelling of hydrologic time series R. Modarres & T. Ouarda 10.1002/hyp.9452
- Evaluation of dynamic regression and artificial neural networks models for real-time hydrological drought forecasting M. Dehghani et al. 10.1007/s12517-017-2990-4
- Rain gauge network design for flood forecasting using multi-criteria decision analysis and clustering techniques in lower Mahanadi river basin, India A. Kar et al. 10.1016/j.ejrh.2015.07.003
- Monthly discharge forecasting using wavelet neural networks with extreme learning machine B. Li & C. Cheng 10.1007/s11431-014-5712-0
- Improving stream flow estimation by incorporating time delay approach in soft computing models V. Garg et al. 10.1080/09715010.2019.1676171
- Genetic Algorithm Driven ANN Model for Runoff Estimation N. Dhamge et al. 10.1016/j.protcy.2012.10.060
- Understanding the Main Causes of Runoff Change by Hydrological Modeling: A Case Study in Luanhe River Basin, North China T. Zhang et al. 10.3390/w10081028
- Artificial Neural Networks for Event Based Rainfall-Runoff Modeling A. Sarkar & R. Kumar 10.4236/jwarp.2012.410105
- A sensitive and efficient method for simultaneous trace detection and identification of triterpene acids and its application to pharmacokinetic study G. Chen et al. 10.1016/j.talanta.2012.06.053
- Comparison of Stabilization Ability of Models for Hydrological Time Series with a Deterministic Trend H. Xie et al. 10.1155/2015/218289
- Monthly evaporation forecasting using artificial neural networks and support vector machines G. Tezel & M. Buyukyildiz 10.1007/s00704-015-1392-3
- A hybrid model to simulate the annual runoff of the Kaidu River in northwest China J. Xu et al. 10.5194/hess-20-1447-2016
- Changes of extreme drought and flood events in Iran R. Modarres et al. 10.1016/j.gloplacha.2016.07.008
- Daily Outflow Prediction by Multi Layer Perceptron with Logistic Sigmoid and Tangent Sigmoid Activation Functions M. Rezaeian Zadeh et al. 10.1007/s11269-009-9573-4
- Accurate Analysis and Evaluation of Acidic Plant Growth Regulators in Transgenic and Nontransgenic Edible Oils with Facile Microwave-Assisted Extraction–Derivatization M. Liu et al. 10.1021/acs.jafc.5b02489
- Impacts of the Three Gorges Dam on the streamflow fluctuations in the downstream region S. Guo et al. 10.1016/j.jhydrol.2021.126480
- A sensitive and efficient method to systematically detect two biophenols in medicinal herb, herbal products and rat plasma based on thorough study of derivatization and its convenient application to pharmacokinetics with semi-automated device G. Chen et al. 10.1016/j.chroma.2012.06.027
- SUITABILITY OF NEURAL NETWORK TECHNIQUES FOR RAINFALL-RUNOFF MODELLING OVER A RIVER BASIN: A COMPREHENSIVE LITERATURE REVIEW K. SANJEEV et al. 10.26634/jfet.13.4.14434
- Development of ultrasonic-assisted closed in-syringe extraction and derivatization for the determination of labile abietic acid and dehydroabietic acid in cosmetics J. Liu et al. 10.1016/j.chroma.2014.10.059
- Nonlinear response of runoff to atmospheric freezing level height variation based on hybrid prediction models Y. Qin et al. 10.1080/02626667.2019.1662023
- Prediction of biochemical oxygen demand at the upstream catchment of a reservoir using adaptive neuro fuzzy inference system Y. Chiu et al. 10.2166/wst.2017.359
- Modelling heteroscedasticty of streamflow times series R. Modarres & T. Ouarda 10.1080/02626667.2012.743662
- Rainfall-runoff modeling in hilly watershed using heuristic approaches with gamma test A. Singh et al. 10.1007/s12517-018-3614-3
- Uncertainty analysis of streamflow drought forecast using artificial neural networks and Monte‐Carlo simulation M. Dehghani et al. 10.1002/joc.3754
- Climate and catchment controls on the performance of regional flood simulations T. Nester et al. 10.1016/j.jhydrol.2011.03.028
- Monthly rainfall–runoff modelling using artificial neural networks F. Machado et al. 10.1080/02626667.2011.559949
- Assessment of a conceptual hydrological model and artificial neural networks for daily outflows forecasting M. Rezaeianzadeh et al. 10.1007/s13762-013-0209-0
- Sensitive, accurate and rapid detection of trace aliphatic amines in environmental samples with ultrasonic-assisted derivatization microextraction using a new fluorescent reagent for high performance liquid chromatography G. Chen et al. 10.1016/j.chroma.2014.05.061
- Validation of an ANN Flow Prediction Model Using a Multistation Cluster Analysis M. Demirel et al. 10.1061/(ASCE)HE.1943-5584.0000426
- Rapid and sensitive ultrasonic-assisted derivatisation microextraction (UDME) technique for bitter taste-free amino acids (FAA) study by HPLC–FLD G. Chen et al. 10.1016/j.foodchem.2013.07.099
- Dynamic versus static neural network model for rainfall forecasting at Klang River Basin, Malaysia A. El-Shafie et al. 10.5194/hess-16-1151-2012
- Analysis of Rainfall-runoff Neuron Input Model with Artificial Neural Network for Simulation for Availability of Discharge at Bah Bolon Watershed . Setiono & R. Hadiani 10.1016/j.proeng.2015.11.022
- Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts D. Harris & W. Li 10.1080/00140139.2017.1407441
- Application of surrogate artificial intelligent models for real‐time flood routing H. Ghalkhani et al. 10.1111/j.1747-6593.2012.00344.x
- Multilayer perceptron with different training algorithms for streamflow forecasting P. Hosseinzadeh Talaee 10.1007/s00521-012-1287-5
- Short‐Term Power Generation Energy Forecasting Model for Small Hydropower Stations Using GA‐SVM G. Li et al. 10.1155/2014/381387
- Prediction of precipitation in Golestan dam watershed using climate signals H. Ruigar & S. Golian 10.1007/s00704-015-1377-2
- A refined automated grain sizing method for estimating river-bed grain size distribution of digital images C. Chung & F. Chang 10.1016/j.jhydrol.2013.01.026
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