Comparative analysis of neural network training algorithms for the flood forecast modelling of an alluvial Himalayan river
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[1] R. Abrahart,et al. Flood estimation at ungauged sites using artificial neural networks , 2006 .
[2] G. Karatzas,et al. A national scale flood hazard mapping methodology: The case of Greece - Protection and adaptation policy approaches. , 2017, The Science of the total environment.
[3] Hirad Abghari,et al. Prediction of monthly discharge volume by different artificial neural network algorithms in semi-arid regions , 2013, Arabian Journal of Geosciences.
[4] Bernard Bobée,et al. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach , 2000 .
[5] Zhang Wenyuan,et al. Land Cover Change Detection in Urban Lake Areas Using Multi-Temporary Very High Spatial Resolution Aerial Images , 2018 .
[6] Jan Adamowski,et al. Comparison of Multivariate Regression and Artificial Neural Networks for Peak Urban Water-Demand Forecasting: Evaluation of Different ANN Learning Algorithms , 2010 .
[7] Giorgio Guariso,et al. Coupling fuzzy modeling and neural networks for river flood prediction , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[8] V. Kale,et al. Climate change and the precipitation variations in the northwestern Himalaya: 1866–2006 , 2010 .
[9] Xiaohong Chen,et al. Flood hazard risk assessment model based on random forest , 2015 .
[10] A-Xing Zhu,et al. Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution. , 2018, The Science of the total environment.
[11] Deepika Yadav,et al. Stream flow forecasting using Levenberg-Marquardt algorithm approach , 2011 .
[12] Stefano Alvisi,et al. Water level forecasting through fuzzy logic and artificial neural network approaches , 2005 .
[13] Farid U. Dowla,et al. Backpropagation Learning for Multilayer Feed-Forward Neural Networks Using the Conjugate Gradient Method , 1991, Int. J. Neural Syst..
[14] Edward Keedwell,et al. Urban flood prediction in real-time from weather radar and rainfall data using artificial neural networks , 2011 .
[15] Shuang Liu,et al. Efficiency enhancement of a process-based rainfall-runoff model using a new modified AdaBoost.RT technique , 2014, Appl. Soft Comput..
[16] H. Pourghasemi,et al. Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms. , 2018, The Science of the total environment.
[17] O. Şenkal. Comparison of Incoming Solar Radiation at Different Air Density Regimes Using Neural Network Models , 2018, Russian Meteorology and Hydrology.
[18] Ming-Chang Wu,et al. A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events , 2017, Appl. Soft Comput..
[19] Özgür Kisi,et al. Performance of radial basis and LM-feed forward artificial neural networks for predicting daily watershed runoff , 2013, Appl. Soft Comput..
[20] Wenzhi Zhao,et al. Comparing the performance of empirical black-box models for river flow forecasting in the Heihe River Basin, Northwestern China , 2014 .
[21] G. Karatzas,et al. Flood management and a GIS modelling method to assess flood-hazard areas—a case study , 2011 .
[22] Ernesto Araujo,et al. Neural network and fuzzy logic statistical downscaling of atmospheric circulation-type specific weather pattern for rainfall forecasting , 2014, Appl. Soft Comput..
[23] D. Jato-Espino,et al. Flood Risk Assessment in Urban Catchments Using Multiple Regression Analysis , 2018 .
[24] Paresh Chandra Deka,et al. Support vector machine applications in the field of hydrology: A review , 2014, Appl. Soft Comput..
[25] Martin Fodslette Møller,et al. A scaled conjugate gradient algorithm for fast supervised learning , 1993, Neural Networks.
[26] M.F.A.M. van Maarseveen,et al. A generalised fuzzy cognitive mapping approach for modelling complex systems , 2019, Appl. Soft Comput..
[27] Mian M. Awais,et al. Predicting weather events using fuzzy rule based system , 2011, Appl. Soft Comput..
[28] M. Imteaz,et al. Seasonal rainfall forecasting by adaptive network-based fuzzy inference system (ANFIS) using large scale climate signals , 2016, Climate Dynamics.
[29] Md. Jalil Piran,et al. Survey of computational intelligence as basis to big flood management: challenges, research directions and future work , 2018 .
[30] George P. Karatzas,et al. Development of a thresholds approach for real‐time flash flood prediction in complex geomorphological river basins , 2012 .
[31] C. Peng,et al. Modelling the impacts of climate and land use changes on soil water erosion: Model applications, limitations and future challenges. , 2019, Journal of environmental management.
[32] Tienfuan Kerh,et al. Neural networks forecasting of flood discharge at an unmeasured station using river upstream information , 2006, Adv. Eng. Softw..
[33] Jan Adamowski,et al. Hybrid artificial intelligence-time series models for monthly streamflow modeling , 2019, Appl. Soft Comput..
[34] Narendra Singh Raghuwanshi,et al. Flood Forecasting Using ANN, Neuro-Fuzzy, and Neuro-GA Models , 2009 .
[35] Bijaya K. Panigrahi,et al. Indian summer monsoon rainfall prediction: A comparison of iterative and non-iterative approaches , 2017, Appl. Soft Comput..
[36] Hubert H. G. Savenije,et al. Hydrological model coupling with ANNs , 2006 .
[37] Kwok-wing Chau,et al. Flood Prediction Using Machine Learning Models: Literature Review , 2018, Water.
[38] Shabir Ahmad,et al. Flood frequency analysis of river Jhelum in Kashmir basin , 2019, Quaternary International.
[39] Sulafa Hag Elsafi. Artificial Neural Networks (ANNs) for flood forecasting at Dongola Station in the River Nile, Sudan , 2014 .
[40] Celso Augusto Guimarães Santos,et al. Analysis of the use of discrete wavelet transforms coupled with ANN for short-term streamflow forecasting , 2019, Appl. Soft Comput..
[41] Stelios Kapetanakis,et al. Artificial Neural Network and Multiple Linear Regression for Flood Prediction in Mohawk River, New York , 2018, Water.
[42] V. A. Kuzmin,et al. Post-processing and forecasts updating in automated systems of flash flood forecasting , 2009 .
[43] S. Sorooshian,et al. A high resolution coupled hydrologic-hydraulic model (HiResFlood-UCI) for flash flood modeling , 2016 .
[44] Zaw Zaw Latt,et al. Improving Flood Forecasting in a Developing Country: A Comparative Study of Stepwise Multiple Linear Regression and Artificial Neural Network , 2014, Water Resources Management.
[45] Ashu Jain,et al. A comparative analysis of training methods for artificial neural network rainfall-runoff models , 2006, Appl. Soft Comput..
[46] Stjepan Lakusic. Application of artificial neural networks for hydrological modelling in Karst , 2018 .
[47] Christian W. Dawson,et al. An artificial neural network approach to rainfall-runoff modelling , 1998 .
[48] E. Nakakita,et al. Flood Forecast and Early Warning with High-Resolution Ensemble Rainfall from Numerical Weather Prediction Model☆ , 2016 .
[49] Florentino Fernández Riverola,et al. A hybrid artificial intelligence model for river flow forecasting , 2013, Appl. Soft Comput..
[50] D. Y. Vasil'ev,et al. Correlation between the total precipitation and the mean and maximum runoff during the snowmelt flood in the Belaya River basin , 2013, Russian Meteorology and Hydrology.
[51] Dieu Tien Bui,et al. A novel hybrid artificial intelligence approach for flood susceptibility assessment , 2017, Environ. Model. Softw..