Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model

[1] Adnan RM(2018)Stream flow forecasting of poorly gauged mountainous watershed by least square support vector machine, fuzzy genetic algorithm and M5 model tree using climatic data from nearby station Water Resour Manage 32 4469-4486

[2] Yuan X(2019)Daily streamflow prediction using optimally pruned extreme learning machine Journal of Hydrology 577 123981-50

[3] Kisi O(2020)Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs J Hydrol 586 124371-931

[4] Adnan M(2020)Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series Stoch Env Res Risk Assess 34 33-597

[5] Mehmood A(2009)Artificial neural network models for forecasting monthly precipitation in Jordan Stoch Environ Res Risk Assess 23 917-12

[6] Adnan RM(2017)A new approach for simulating and forecasting the rainfall-runoff process within the next two months J Hydrol 548 588-1216

[7] Liang Z(2019)Development of multivariate adaptive regression spline integrated with differential evoltion model for streamflow simulation J Hydrol 573 1-27

[8] Trajkovic S(2006)Rainfall–runoff modeling using artificial neural networks technique: a Blue Nile catchment case study Hydrol Process 20 1201-398

[9] Zounemat-Kermani M(2009)Applying wavelets to short-term load forecasting using PSO-based neural networks IEEE Trans Power Syst 24 20-1767

[10] Li B(2002)Performance of neural networks in daily streamflow forecasting J Hydrol Eng 7 392-656

[1] Adnan RM(2018)Stream flow forecasting of poorly gauged mountainous watershed by least square support vector machine, fuzzy genetic algorithm and M5 model tree using climatic data from nearby station Water Resour Manage 32 4469-4486

[2] Yuan X(2019)Daily streamflow prediction using optimally pruned extreme learning machine Journal of Hydrology 577 123981-50

[3] Kisi O(2020)Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs J Hydrol 586 124371-931

[4] Adnan M(2020)Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series Stoch Env Res Risk Assess 34 33-597

[5] Mehmood A(2009)Artificial neural network models for forecasting monthly precipitation in Jordan Stoch Environ Res Risk Assess 23 917-12

[6] Adnan RM(2017)A new approach for simulating and forecasting the rainfall-runoff process within the next two months J Hydrol 548 588-1216

[7] Liang Z(2019)Development of multivariate adaptive regression spline integrated with differential evoltion model for streamflow simulation J Hydrol 573 1-27

[8] Trajkovic S(2006)Rainfall–runoff modeling using artificial neural networks technique: a Blue Nile catchment case study Hydrol Process 20 1201-398

[9] Zounemat-Kermani M(2009)Applying wavelets to short-term load forecasting using PSO-based neural networks IEEE Trans Power Syst 24 20-1767

[10] Li B(2002)Performance of neural networks in daily streamflow forecasting J Hydrol Eng 7 392-656