Streamflow forecasting
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[1] Enli Wang,et al. Monthly and seasonal streamflow forecasts using rainfall‐runoff modeling and historical weather data , 2011 .
[2] Ahmad Sharafati,et al. Complementary data-intelligence model for river flow simulation , 2018, Journal of Hydrology.
[3] A. Jayawardena,et al. Noise reduction and prediction of hydrometeorological time series: dynamical systems approach vs. stochastic approach , 2000 .
[4] W. El-Dakhakhni,et al. Hybrid Hydrological Data-Driven Approach for Daily Streamflow Forecasting , 2020 .
[5] Zakari Seybou Abdourahamane,et al. Wavelet–copula‐based mutual information for rainfall forecasting applications , 2019, Hydrological Processes.
[6] Yuqiong Liu,et al. A wavelet-based approach to assessing timing errors in hydrologic predictions , 2011 .
[7] Slobodan P. Simonovic,et al. Short term streamflow forecasting using artificial neural networks , 1998 .
[8] Vahid Nourani,et al. Multi-station streamflow forecasting using wavelet denoising and artificial intelligence models , 2017 .
[9] Mohammad Ali Ghorbani,et al. Integration of Volterra model with artificial neural networks for rainfall-runoff simulation in forested catchment of northern Iran , 2016 .
[10] Wenrui Huang,et al. Forecasting flows in Apalachicola River using neural networks , 2004 .
[11] Jan Adamowski,et al. Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. , 2010 .
[12] J. Adamowski,et al. A comparison of conventional and wavelet transform based methods for streamflow record extension , 2020 .
[13] Mir Jafar Sadegh Safari,et al. Hybrid models to improve the monthly river flow prediction: Integrating artificial intelligence and non-linear time series models , 2019, Journal of Hydrology.
[14] Ozgur Kisi,et al. Wavelet-linear genetic programming: A new approach for modeling monthly streamflow , 2017 .
[15] V. Jothiprakash,et al. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data , 2012 .
[16] Ali Danandeh Mehr,et al. Successive-station monthly streamflow prediction using neuro-wavelet technique , 2014, Earth Science Informatics.
[17] W. Pitts,et al. A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.
[18] Jungang Luo,et al. Decomposition ensemble model based on variational mode decomposition and long short-term memory for streamflow forecasting , 2020 .
[19] O. Kisi. Wavelet regression model for short-term streamflow forecasting. , 2010 .
[20] J. Bonné. Stochastic simulation of monthly streamflow by a multiple regression model utilizing precipitation data , 1971 .
[21] R. Dehghani,et al. Daily streamflow prediction using support vector machine-artificial flora (SVM-AF) hybrid model , 2020, Acta Geophysica.
[22] B. Akintug,et al. A Markov switching model for annual hydrologic time series , 2005 .
[23] Kuolin Hsu,et al. Improved streamflow forecasting using self-organizing radial basis function artificial neural networks , 2004 .
[24] Wen Wang,et al. Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes , 2005 .
[25] Jyh-Shing Roger Jang,et al. ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..
[26] X. Wen,et al. A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region , 2014 .
[27] C. Sim. A mixed gamma ARMA(1, 1) Model for river flow time series , 1987 .
[28] Shalamu Abudu,et al. Application of Partial Least-Squares Regression in Seasonal Streamflow Forecasting , 2010 .
[29] Indrajeet Chaubey,et al. Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed , 2008 .
[30] James M. Ehrman,et al. Using neural networks to assess the influence of changing seasonal climates in modifying discharge, dissolved organic carbon, and nitrogen export in eastern Canadian rivers , 1998 .
[31] J J Hopfield,et al. Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.
[32] R. Maheswaran,et al. Wavelet–Volterra coupled model for monthly stream flow forecasting , 2012 .
[33] Chandranath Chatterjee,et al. A new wavelet-bootstrap-ANN hybrid model for daily discharge forecasting , 2011 .
[34] Farshad Fathian,et al. Modeling streamflow time series using nonlinear SETAR-GARCH models , 2019, Journal of Hydrology.
[35] M. Valipour. Long‐term runoff study using SARIMA and ARIMA models in the United States , 2015 .
[36] Jose D. Salas,et al. Modeling of streamflow processes at different time scales , 1993 .
[37] T. Sathish,et al. River Flow Forecasting using Recurrent Neural Networks , 2004 .
[38] O. Kisi,et al. Support vector regression optimized by meta-heuristic algorithms for daily streamflow prediction , 2020, Stochastic Environmental Research and Risk Assessment.
[39] R. Deo,et al. An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland , 2016, Environmental Monitoring and Assessment.
[40] J. P. Matos,et al. Towards Safer Data-Driven Forecasting of Extreme Streamflows , 2017, Water Resources Management.
[41] R. Abrahart,et al. Comparing neural network and autoregressive moving average techniques for the provision of continuous river flow forecasts in two contrasting catchments , 2000 .
[42] P. P. Mujumdar,et al. Stochastic models of streamflow: some case studies , 1990 .
[43] Adarsh Singh,et al. Daily river flow forecasting using wavelet ANN hybrid models , 2010 .
[44] Alireza B. Dariane,et al. Streamflow forecasting by combining neural networks and fuzzy models using advanced methods of input variable selection , 2018 .
[45] P. Deka,et al. Performance enhancement of SVM model using discrete wavelet transform for daily streamflow forecasting , 2021, Environmental Earth Sciences.
[46] S. Kanae,et al. Global Hydrological Cycles and World Water Resources , 2006, Science.
[47] André Gustavo da Silva Melo Honorato,et al. Monthly streamflow forecasting using neuro-wavelet techniques and input analysis , 2018, Hydrological Sciences Journal.
[48] Stan Openshaw,et al. A hybrid multi-model approach to river level forecasting , 2000 .
[49] Nguyen Thi Thuy Linh,et al. Adaptive neuro-fuzzy inference system coupled with shuffled frog leaping algorithm for predicting river streamflow time series , 2020 .
[50] D. K. Srivastava,et al. Application of ANN for Reservoir Inflow Prediction and Operation , 1999 .
[51] Vijay P. Singh,et al. A multiple-input single-output model for flow forecasting , 1999 .
[52] Jose D. Salas,et al. Estimation of ARMA Models with seasonal parameters , 1982 .
[53] Juan B. Valdés,et al. Streamflow Forecasting for Han River Basin, Korea , 1994 .
[54] J. Amorocho,et al. Determination of Nonlinear Functional Response Functions in Rainfall-Runoff Processes , 1971 .
[55] Rameswar Panda,et al. Application of neural network and adaptive neuro-fuzzy inference systems for river flow prediction , 2009 .
[56] P. C. Nayak,et al. Fuzzy computing based rainfall–runoff model for real time flood forecasting , 2005 .
[57] Amir AghaKouchak,et al. A hybrid framework for assessing socioeconomic drought: Linking climate variability, local resilience, and demand , 2015 .
[58] Edward A. McBean,et al. River Flow Forecasting Model For Sturgeon River , 1985 .
[59] Ahmed El-Shafie,et al. A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam , 2007 .
[60] Zaher Mundher Yaseen,et al. Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model , 2017 .
[61] R. Deo,et al. Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq , 2016 .
[62] Jan Adamowski,et al. Multiscale streamflow forecasting using a new Bayesian Model Average based ensemble multi-wavelet Volterra nonlinear method , 2013 .
[63] Ahmed El-Shafie,et al. Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm , 2020 .
[64] A. Shamseldin,et al. Methods for combining the outputs of different rainfall–runoff models , 1997 .
[65] Karim C. Abbaspour,et al. A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows , 2013 .
[66] D. Dickey,et al. Testing for unit roots in autoregressive-moving average models of unknown order , 1984 .
[67] Zhiyong Liu,et al. Evaluating a coupled discrete wavelet transform and support vector regression for daily and monthly streamflow forecasting , 2014 .
[68] Lotfi A. Zadeh,et al. Fuzzy Sets , 1996, Inf. Control..
[69] Vladan Babovic,et al. Rainfall runoff modelling based on genetic programming , 2002 .
[70] K. W. Chau,et al. Eutrophication Model for a Coastal Bay in Hong Kong , 1998 .
[71] Upmanu Lall,et al. A Nearest Neighbor Bootstrap For Resampling Hydrologic Time Series , 1996 .
[72] Ashu Jain,et al. Hybrid neural network models for hydrologic time series forecasting , 2007, Appl. Soft Comput..
[73] Makarand Deo,et al. Real‐Time Flood Forecasting Using Neural Networks , 1998 .
[74] Özgür Kişi,et al. Daily River Flow Forecasting Using Artificial Neural Networks and Auto-Regressive Models , 2005 .
[75] Keith W. Hipel,et al. Forecasting annual geophysical time series , 1988 .
[76] W. Alley. Water Balance Models in One‐Month‐Ahead Streamflow Forecasting , 1985 .
[77] G. Yule. On a Method of Investigating Periodicities in Disturbed Series, with Special Reference to Wolfer's Sunspot Numbers , 1927 .
[78] Soroosh Sorooshian,et al. Modeling and simulating of reservoir operation using the artificial neural network, support vector regression, deep learning algorithm , 2018, Journal of Hydrology.
[79] Giha Lee,et al. Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting , 2019, Water.
[80] D. Garen. Improved Techniques in Regression‐Based Streamflow Volume Forecasting , 1992 .
[81] S. K. Mittal,et al. Stochastic modelling of rainfall and runoff phenomenon: a time series approach review , 2014 .
[82] K. P. Sudheer,et al. Short‐term flood forecasting with a neurofuzzy model , 2005 .
[83] Chris Chatfield,et al. Holt‐Winters Forecasting: Some Practical Issues , 1988 .
[84] Mac McKee,et al. Adjusting wavelet‐based multiresolution analysis boundary conditions for long‐term streamflow forecasting , 2016 .
[85] Absolute and relative measures for evaluating the forecasting performance of time series models for daily streamflows , 2006 .
[86] Shaozhong Kang,et al. Integrated neural networks for monthly river flow estimation in arid inland basin of Northwest China , 2012 .
[87] Hafzullah Aksoy,et al. Markov chain-based modeling techniques for stochastic generation of daily intermittent streamflows , 2003 .
[88] A. I. McLeod,et al. Kalman filter estimation for periodic autoregressive-moving average models , 1989 .
[89] J. Delleur,et al. Application of seasonal parametric linear stochastic models to monthly flow data , 1974 .
[90] J. Salas,et al. SHORT‐TERM FORECASTING OF SNOWMELT RUNOFF USING ARMAX MODELS1 , 1988 .
[91] S. L. Jacoby. A mathematical model for nonlinear hydrologic systems , 1966 .
[92] Hui-Chen Su,et al. A nonlinear time series analysis using two‐stage genetic algorithms for streamflow forecasting , 2008 .
[93] A. Farokhnia,et al. A hybrid of Random Forest and Deep Auto-Encoder with support vector regression methods for accuracy improvement and uncertainty reduction of long-term streamflow prediction , 2020 .
[94] P. Gelder,et al. Forecasting daily streamflow using hybrid ANN models , 2006 .
[95] Donald C. Wunsch,et al. Advanced neural network training methods for low false alarm stock trend prediction , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).
[96] A. Danandeh Mehr,et al. Successive-station monthly streamflow prediction using different artificial neural network algorithms , 2015, International Journal of Environmental Science and Technology.
[97] K. Chau,et al. Three-dimensional pollutant transport model for the Pearl River Estuary. , 2002, Water research.
[98] Gustavo Barbosa Lima da Silva,et al. Daily streamflow forecasting using a wavelet transform and artificial neural network hybrid models , 2014 .
[99] V. V. Srinivas,et al. Post-blackening approach for modeling dependent annual streamflows , 2000 .
[100] Ozgur Kisi,et al. Prediction of river flow using hybrid neuro-fuzzy models , 2018, Arabian Journal of Geosciences.
[101] Vladan Babovic,et al. Development of a modular streamflow model to quantify runoff contributions from different land uses in tropical urban environments using Genetic Programming , 2015 .
[102] M. Taqqu,et al. Fractionally differenced ARIMA models applied to hydrologic time series: Identification, estimation, and simulation , 1997 .
[103] Z. Hao,et al. Entropy‐copula method for single‐site monthly streamflow simulation , 2012 .
[104] Seyed-Mohammad Hosseini-Moghari,et al. Development of a Hybrid Data Driven Model for Hydrological Estimation , 2018, Water Resources Management.
[105] Donna M. Rizzo,et al. Advances in ungauged streamflow prediction using artificial neural networks , 2010 .
[106] Mustafa Erkan Turan,et al. Fuzzy Systems Tuned By Swarm Based Optimization Algorithms for Predicting Stream flow , 2016, Water Resources Management.
[107] Dingfang Li,et al. Exploring the Regional Variance using ARMA-GARCH Models , 2016, Water Resources Management.
[108] Chuntian Cheng,et al. A comparison of performance of several artificial intelligence , 2009 .
[109] Aliasghar Montazar,et al. Optimize of all Effective Infiltration Parameters in Furrow Irrigation Using Visual Basic and Genetic Algorithm Programming , 2012 .
[110] Q. Tan,et al. An adaptive middle and long-term runoff forecast model using EEMD-ANN hybrid approach , 2018, Journal of Hydrology.
[111] Ali Danandeh Mehr,et al. Linear genetic programming application for successive-station monthly streamflow prediction , 2014, Comput. Geosci..
[112] T. Ouarda,et al. Modeling rainfall–runoff relationship using multivariate GARCH model , 2013 .
[113] Zaher Mundher Yaseen,et al. Application of the Hybrid Artificial Neural Network Coupled with Rolling Mechanism and Grey Model Algorithms for Streamflow Forecasting Over Multiple Time Horizons , 2018, Water Resources Management.
[114] Mark M. Meerschaert,et al. Identification of periodic autoregressive moving average models and their application to the modeling of river flows , 2006 .
[115] Jingjing Xie,et al. Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models , 2016 .
[116] A. B. Dariane,et al. Long Term Streamflow Forecasting Using a Hybrid Entropy Model , 2018, Water Resources Management.
[117] D. Solomatine,et al. Model trees as an alternative to neural networks in rainfall—runoff modelling , 2003 .
[118] O. Kisi,et al. Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model , 2010 .
[119] Kwok-wing Chau,et al. Improving Forecasting Accuracy of Annual Runoff Time Series Using ARIMA Based on EEMD Decomposition , 2015, Water Resources Management.
[120] Nguyen Thi Thuy Linh,et al. Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm , 2020, Soft Computing.
[121] Narendra Singh Raghuwanshi,et al. Flood Forecasting Using ANN, Neuro-Fuzzy, and Neuro-GA Models , 2009 .
[122] Vahid Nourani,et al. Season Algorithm-Multigene Genetic Programming: A New Approach for Rainfall-Runoff Modelling , 2018, Water Resources Management.
[123] W. Farmer. Ordinary kriging as a tool to estimate historical daily streamflow records , 2016 .
[124] Sinan Jasim Hadi,et al. Monthly streamflow forecasting using continuous wavelet and multi-gene genetic programming combination , 2018, Journal of Hydrology.
[125] Mark M. Meerschaert,et al. Modeling river flows with heavy tails , 1998 .
[126] Daniel Rivero,et al. Prediction and modeling of the rainfall-runoff transformation of a typical urban basin using ann and gp , 2003, Appl. Artif. Intell..
[127] Wenyan Wu,et al. Streamflow prediction using LASSO-FCM-DBN approach based on hydro-meteorological condition classification , 2020 .
[128] Jan Adamowski,et al. Hybrid artificial intelligence-time series models for monthly streamflow modeling , 2019, Appl. Soft Comput..
[129] Yue‐Ping Xu,et al. AI-based techniques for multi-step streamflow forecasts: Application for multi-objective reservoir operation optimization and performance assessment , 2020, Hydrology and Earth System Sciences.
[130] Alpaslan Yarar,et al. A Hybrid Wavelet and Neuro-Fuzzy Model for Forecasting the Monthly Streamflow Data , 2014, Water Resources Management.
[131] Chi Zhang,et al. Are hybrid models integrated with data preprocessing techniques suitable for monthly streamflow forecasting? Some experiment evidences , 2015 .
[132] K. N. Tiwari,et al. Bootstrap based artificial neural network (BANN) analysis for hierarchical prediction of monthly runoff in Upper Damodar Valley Catchment , 2009 .
[133] Teuvo Kohonen,et al. An introduction to neural computing , 1988, Neural Networks.
[134] Inmaculada Pulido-Calvo,et al. Application of neural approaches to one-step daily flow forecasting in Portuguese watersheds , 2007 .
[135] Wen-jing Niu,et al. Monthly runoff time series prediction by variational mode decomposition and support vector machine based on quantum-behaved particle swarm optimization , 2020 .
[136] R. E. Kalman,et al. A New Approach to Linear Filtering and Prediction Problems , 2002 .
[137] Yen-Chang Chen,et al. A counterpropagation fuzzy-neural network modeling approach to real time streamflow prediction , 2001 .
[138] Mahesh Pal,et al. Performance evaluation of artificial neural network approaches in forecasting reservoir inflow , 2012 .
[139] Il Won Seo,et al. Artificial neural network ensemble modeling with exploratory factor analysis for streamflow forecasting , 2015 .
[140] S. Vedula,et al. Multiplicative seasonal Arima model for longterm forecasting of inflows , 1995 .
[141] O. Kisi,et al. Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs , 2020 .
[142] Hui Qin,et al. Monthly streamflow forecasting based on hidden Markov model and Gaussian Mixture Regression , 2018, Journal of Hydrology.
[143] Jose D. Salas,et al. Estimation and validation of contemporaneous PARMA Models for streamflow simulation , 1996 .
[144] Ozgur Kisi,et al. Stream flow forecasting using neuro‐wavelet technique , 2008 .
[145] Puteh Saad,et al. River flow time series using least squares support vector machines , 2011 .
[146] Sidney Yakowitz,et al. A nonparametric Markov Model for daily river flow , 1979 .
[147] O. Kisi,et al. Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence , 2016, Water Resources Management.
[148] Xueqing Zhang,et al. A data-driven model based on Fourier transform and support vector regression for monthly reservoir inflow forecasting , 2018 .
[149] Hossein Bonakdari,et al. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach , 2017, Journal of Earth System Science.
[150] Avi Ostfeld,et al. Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions , 2014, Environ. Model. Softw..
[151] Jose D. Salas,et al. APPROACHES TO MULTIVARIATE MODELING OF WATER RESOURCES TIME SERIES1 , 1985 .
[152] Ronny Berndtsson,et al. Interpolating monthly precipitation by self-organizing map (SOM) and multilayer perceptron (MLP) , 2007 .
[153] Hikmet Kerem Cigizoglu,et al. Application of Generalized Regression Neural Networks to Intermittent Flow Forecasting and Estimation , 2005 .
[154] Hossein Bonakdari,et al. Forecasting monthly inflow with extreme seasonal variation using the hybrid SARIMA-ANN model , 2017, Stochastic Environmental Research and Risk Assessment.
[155] Yan Li,et al. Comparison of Several Flood Forecasting Models in Yangtze River , 2005 .
[156] Heung Wong,et al. Streamflow forecasting using functional-coefficient time series model with periodic variation. , 2009 .
[157] Radko Mesiar,et al. Comparison of forecasting performance of nonlinear models of hydrological time series , 2006 .
[158] Mahmud Güngör,et al. Hydrological time‐series modelling using an adaptive neuro‐fuzzy inference system , 2008 .
[159] Kuolin Hsu,et al. Artificial Neural Network Modeling of the Rainfall‐Runoff Process , 1995 .
[160] Ozgur Kisi,et al. Intermittent Streamflow Forecasting by Using Several Data Driven Techniques , 2011, Water Resources Management.
[161] Soroosh Sorooshian,et al. Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information , 2017 .
[162] Sean W. Fleming,et al. Streamflow Modelling: A Primer on Applications, Approaches and Challenges , 2012 .
[163] Keith W. Hipel,et al. Forecasting monthly riverflow time series , 1985 .
[164] Ozgur Kisi,et al. Applications of hybrid wavelet–Artificial Intelligence models in hydrology: A review , 2014 .
[165] Marcella Niglio,et al. Multi-step SETARMA predictors in the analysis of hydrological time series , 2006 .
[166] Gordon H. Huang,et al. An integrated Bayesian least-squares-support-vector-machine factorial-analysis (B-LSVM-FA) method for inferring inflow from the Amu Darya to the Aral Sea under ensemble prediction , 2021 .
[167] Yufeng Ren,et al. Monthly Mean Streamflow Prediction Based on Bat Algorithm-Support Vector Machine , 2016 .
[168] Lei Ye,et al. Coupling Forecast Methods of Multiple Rainfall–Runoff Models for Improving the Precision of Hydrological Forecasting , 2015, Water Resources Management.
[169] A. A. Harms,et al. An extension to the Thomas‐Fiering Model for the sequential generation of streamflow , 1967 .
[170] Vijay P. Singh,et al. Black-Box Hydrological Models , 2017 .
[171] Zaher Mundher Yaseen,et al. Artificial intelligence based models for stream-flow forecasting: 2000-2015 , 2015 .
[172] Elcin Kentel. Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates , 2009 .
[173] Chandranath Chatterjee,et al. A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products , 2016 .
[174] Zaher Mundher Yaseen,et al. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review , 2017, Theoretical and Applied Climatology.
[175] Keith W. Hipel,et al. Advances in Box‐Jenkins modeling: 2. Applications , 1977 .
[176] Christian W. Dawson,et al. Hydrological modelling using artificial neural networks , 2001 .
[177] R. Vogel,et al. The moving blocks bootstrap versus parametric time series models , 1996 .
[178] Mohammed A. Elganiny,et al. Enhancing the Forecasting of Monthly Streamflow in the Main Key Stations of the River Nile Basin , 2018, Water Resources.
[179] Mohammad Ali Ghorbani,et al. Chaos-based multigene genetic programming: A new hybrid strategy for river flow forecasting , 2018, Journal of Hydrology.
[180] Turgay PartalT. Partal. River flow forecasting using different artificial neural network algorithms and wavelet transform , 2009 .
[181] A. D. Mehr. An improved gene expression programming model for streamflow forecasting in intermittent streams , 2018 .
[182] Alberto Montanari,et al. Modelling hydrological data with and without long memory , 1996 .
[183] Vijay P. Singh,et al. Maximum entropy spectral analysis for streamflow forecasting , 2016 .
[184] Bernard Bobée,et al. Daily reservoir inflow forecasting using artificial neural networks with stopped training approach , 2000 .
[185] Jun Qiu,et al. Long‐term streamflow forecasting using artificial neural network based on preprocessing technique , 2019, Journal of Forecasting.
[186] Jun Qiu,et al. Decomposition-ANN Methods for Long-Term Discharge Prediction Based on Fisher’s Ordered Clustering with MESA , 2019, Water Resources Management.
[187] Y. Liu,et al. Long-Term Streamflow Forecasting Based on Relevance Vector Machine Model , 2016 .
[188] A. Jayawardena,et al. Analysis and prediction of chaos in rainfall and stream flow time series , 1994 .
[189] Jiancang Xie,et al. Daily Runoff Forecasting Using a Hybrid Model Based on Variational Mode Decomposition and Deep Neural Networks , 2019, Water Resources Management.
[190] Nachimuthu Karunanithi,et al. Neural Networks for River Flow Prediction , 1994 .
[191] M. Azmi,et al. Improving the Accuracy of K-Nearest Neighbour Method in Long Lead Hydrological Forecasting , 2016 .
[192] P. Hosseinzadeh Talaee. Multilayer perceptron with different training algorithms for streamflow forecasting , 2014 .
[193] Shengzhi Huang,et al. Monthly streamflow prediction using modified EMD-based support vector machine , 2014 .
[194] V. V. Srinivas,et al. A hybrid stochastic model for multiseason streamflow simulation , 2001 .
[195] Vijay P. Singh,et al. A univariate model for long-term streamflow forecasting: 1. Development , 1991 .
[196] Bin Wang,et al. CEREF: A hybrid data-driven model for forecasting annual streamflow from a socio-hydrological system , 2016 .
[197] H. Raman,et al. Multivariate modelling of water resources time series using artificial neural networks , 1995 .
[198] M. Najarchi,et al. Daily flow forecasting of perennial rivers in an arid watershed: a hybrid ensemble decomposition approach integrated with computational intelligence techniques , 2020, Journal of Water Supply: Research and Technology-Aqua.
[199] Paulin Coulibaly,et al. Improving Daily Reservoir Inflow Forecasts with Model Combination , 2005 .
[200] Vijay P. Singh,et al. A univariate model for long-term streamflow forecasting , 1991 .
[201] K. Chau,et al. Predicting monthly streamflow using data‐driven models coupled with data‐preprocessing techniques , 2009 .
[202] E. Toth,et al. Comparison of short-term rainfall prediction models for real-time flood forecasting , 2000 .
[203] Jason Smith,et al. Neural-Network Models of Rainfall-Runoff Process , 1995 .
[204] null null,et al. Artificial Neural Networks in Hydrology. II: Hydrologic Applications , 2000 .
[205] C. Holt. Author's retrospective on ‘Forecasting seasonals and trends by exponentially weighted moving averages’ , 2004 .
[206] Zhanya Xu,et al. A hybrid support vector regression framework for streamflow forecast , 2019, Journal of Hydrology.
[207] Johannes Ledolter,et al. A general class of stochastic models for hydrologic sequences , 1978 .
[208] Yen-Ming Chiang,et al. Comparison of static-feedforward and dynamic-feedback neural networks for rainfall -runoff modeling , 2004 .
[209] Nelson Obregón-Neira,et al. Forecasting of Monthly Streamflows Based on Artificial Neural Networks , 2009 .
[210] Shie-Yui Liong,et al. Flow categorization model for improving forecasting , 2005 .
[211] Linda See,et al. Data preprocessing for river flow forecasting using neural networks: Wavelet transforms and data partitioning , 2006 .
[212] Zhong-kai Feng,et al. Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction , 2021 .
[213] A. M. Al-Juboori. A Hybrid Model to Predict Monthly Streamflow Using Neighboring Rivers Annual Flows , 2021, Water Resources Management.
[214] Ali Danandeh Mehr,et al. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction , 2017 .
[215] D. G. Watts,et al. Application of Linear Random Models to Four Annual Streamflow Series , 1970 .
[216] Aman Mohammad Kalteh,et al. Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform , 2013, Comput. Geosci..
[217] Aytac Guven,et al. Linear genetic programming for time-series modelling of daily flow rate , 2009 .
[218] Aranildo R. Lima,et al. Forecasting daily streamflow using online sequential extreme learning machines , 2016 .
[219] Fu Chao Liu,et al. Hybrid forecasting model for non-stationary daily runoff series: A case study in the Han River Basin, China , 2019, Journal of Hydrology.
[220] Florentino Fernández Riverola,et al. A hybrid artificial intelligence model for river flow forecasting , 2013, Appl. Soft Comput..
[221] A. Grossmann,et al. DECOMPOSITION OF HARDY FUNCTIONS INTO SQUARE INTEGRABLE WAVELETS OF CONSTANT SHAPE , 1984 .
[222] Kwok-Wing Chau,et al. Data-driven models for monthly streamflow time series prediction , 2010, Eng. Appl. Artif. Intell..
[223] Kwok-wing Chau,et al. A novel hybrid neural network based on continuity equation and fuzzy pattern-recognition for downstream daily river discharge forecasting , 2015 .
[224] Peter R. Winters,et al. Forecasting Sales by Exponentially Weighted Moving Averages , 1960 .
[225] N. Null. Artificial Neural Networks in Hydrology. I: Preliminary Concepts , 2000 .
[226] K. P. Sudheer,et al. A hybrid linear‐neural model for river flow forecasting , 2006 .
[227] Everette S. Gardner,et al. Exponential smoothing: The state of the art , 1985 .
[228] K. P. Sudheer,et al. A nonlinear data‐driven model for synthetic generation of annual streamflows , 2008 .
[229] Z. Yaseen,et al. Novel Hybrid Data-Intelligence Model for Forecasting Monthly Rainfall with Uncertainty Analysis , 2019, Water.
[230] O. Kisi. River flow forecasting and estimation using different artificial neural network techniques , 2008 .
[231] Honey Badrzadeh,et al. Impact of multi-resolution analysis of artificial intelligence models inputs on multi-step ahead river flow forecasting , 2013 .
[232] K. Trenberth,et al. Climate Variability and Global Warming , 2001, Science.
[233] Zaher Mundher Yaseen,et al. An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction , 2019, Journal of Hydrology.
[234] M. Taqqu,et al. Estimating long-range dependence in the presence of periodicity: An empirical study , 1999 .
[235] Özlem Terzi,et al. Forecasting of monthly river flow with autoregressive modeling and data-driven techniques , 2013, Neural Computing and Applications.
[236] Ahmad Sharafati,et al. Development of multivariate adaptive regression spline integrated with differential evolution model for streamflow simulation , 2019, Journal of Hydrology.
[237] Milan Stojković,et al. A joint stochastic-deterministic approach for long-term and short-term modelling of monthly flow rates , 2017 .
[238] Soichi Nishiyama,et al. A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff , 2007 .
[239] Pao-Shan Yu,et al. A model to forecast flow with uncertainty analysis , 1996 .
[240] Ozgur Kisi,et al. Streamflow Forecasting Using Different Artificial Neural Network Algorithms , 2007 .
[241] S. Shamshirband,et al. Support Vector Regression Integrated with Fruit Fly Optimization Algorithm for River Flow Forecasting in Lake Urmia Basin , 2019, Water.
[242] Pariva Dobriyal,et al. A review of methods for monitoring streamflow for sustainable water resource management , 2017, Applied Water Science.
[243] W S McCulloch,et al. A logical calculus of the ideas immanent in nervous activity , 1990, The Philosophy of Artificial Intelligence.
[244] Asaad Y. Shamseldin,et al. A non-linear combination of the forecasts of rainfall-runoff models by the first-order Takagi–Sugeno fuzzy system , 2001 .
[245] Ozgur Kisi,et al. River Flow Estimation and Forecasting by Using Two Different Adaptive Neuro-Fuzzy Approaches , 2012, Water Resources Management.
[246] K. Thirumalaiah,et al. Hydrological Forecasting Using Neural Networks , 2000 .
[247] K. Lindenschmidt,et al. Review of the application of fuzzy inference systems in river flow forecasting , 2009 .
[248] Li Wen,et al. Reconstruction natural flow in a regulated system, the Murrumbidgee River, Australia, using time series analysis , 2009 .
[249] Ozgur Kisi,et al. River Flow Modeling Using Artificial Neural Networks , 2004 .
[250] Avi Ostfeld,et al. Data-driven modelling: some past experiences and new approaches , 2008 .
[251] A. Kalteh. Wavelet Genetic Algorithm-Support Vector Regression (Wavelet GA-SVR) for Monthly Flow Forecasting , 2015, Water Resources Management.
[252] Slobodan P. Simonovic,et al. Estimation of missing streamflow data using principles of chaos theory , 2002 .
[253] M. Valipour,et al. Hybrid MARMA-NARX model for flow forecasting based on the large-scale climate signals, sea-surface temperatures, and rainfall , 2018, Hydrology Research.
[254] G. S. Dwarakish,et al. A Review on Hydrological Models , 2015 .
[255] Honey Badrzadeh,et al. Improving Ann‐Based Short‐Term and Long‐Term Seasonal River Flow Forecasting with Signal Processing Techniques , 2016 .
[256] Dong Wang,et al. Streamflow forecasting using extreme gradient boosting model coupled with Gaussian mixture model , 2020 .
[257] Saeid Mehdizadeh,et al. A Comparative Study of Autoregressive, Autoregressive Moving Average, Gene Expression Programming and Bayesian Networks for Estimating Monthly Streamflow , 2018, Water Resources Management.
[258] Amir Mosavi,et al. Monthly streamflow prediction using a hybrid stochastic-deterministic approach for parsimonious non-linear time series modeling , 2020 .
[259] Umut Okkan,et al. The combined use of wavelet transform and black box models in reservoir inflow modeling , 2013 .
[260] Ani Shabri,et al. Streamflow forecasting using least-squares support vector machines , 2012 .
[261] Fang-Fang Li,et al. Hybrid Models Combining EMD/EEMD and ARIMA for Long-Term Streamflow Forecasting , 2018, Water.
[262] AR-GARCH with Exogenous Variables as a Postprocessing Model for Improving Streamflow Forecasts , 2020 .
[263] Balaji Rajagopalan,et al. Modified K-NN Model for Stochastic Streamflow Simulation , 2006 .
[264] L. Karthikeyan,et al. Predictability of nonstationary time series using wavelet and EMD based ARMA models , 2013 .
[265] Peyman Abbaszadeh,et al. Development of a coupled wavelet transform and evolutionary Levenberg‐Marquardt neural networks for hydrological process modeling , 2018, Comput. Intell..
[266] Kwok-wing Chau,et al. Particle Swarm Optimization Training Algorithm for ANNs in Stage Prediction of Shing Mun River , 2006 .
[267] M. Valipour,et al. Comparison of the ARMA, ARIMA, and the autoregressive artificial neural network models in forecasting the monthly inflow of Dez dam reservoir , 2013 .
[268] Alexander Y. Sun,et al. Monthly streamflow forecasting using Gaussian Process Regression , 2014 .
[269] K. P. Sudheer,et al. A neuro-fuzzy computing technique for modeling hydrological time series , 2004 .
[270] Chu Zhang,et al. Data Pre-Analysis and Ensemble of Various Artificial Neural Networks for Monthly Streamflow Forecasting , 2018 .
[271] Jose D. Salas,et al. Gamma‐Autoregressive Models for Stream‐Flow Simulation , 1990 .
[272] K. P. Sudheer,et al. Potential application of wavelet neural network ensemble to forecast streamflow for flood management , 2016 .
[273] Jose D. Salas,et al. Streamflow Forecasting Based on Artificial Neural Networks , 2000 .
[274] Holger R. Maier,et al. Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river , 2005 .
[275] M. Castellano-Méndez,et al. Modelling of the monthly and daily behaviour of the runoff of the Xallas river using Box-Jenkins and neural networks methods , 2004 .
[276] Sheng Chen,et al. Sparse support vector regression based on orthogonal forward selection for the generalised kernel model , 2006, Neurocomputing.
[277] Esmail Amiri,et al. Forecasting daily river flows using nonlinear time series models , 2015 .
[278] Qiang Zhang,et al. Univariate streamflow forecasting using commonly used data-driven models: literature review and case study , 2018 .
[279] Aboelmagd Noureldin,et al. Acclimatizing Fast Orthogonal Search (FOS) Model for River Stream-flow Forecasting , 2016 .
[280] Chuntian Cheng,et al. Using support vector machines for long-term discharge prediction , 2006 .
[281] Qiang Zhang,et al. Singular Spectrum Analysis and ARIMA Hybrid Model for Annual Runoff Forecasting , 2011 .
[282] Jin Zhang,et al. Short-Term Streamflow Forecasting Using the Feature-Enhanced Regression Model , 2019, Water Resources Management.
[283] Dimitri P. Solomatine,et al. Data-Driven Modelling: Concepts, Approaches and Experiences , 2009 .
[284] Armando Brath,et al. Multistep ahead streamflow forecasting: Role of calibration data in conceptual and neural network modeling , 2007 .
[285] Philip Hans Franses,et al. A seasonal periodic long memory model for monthly river flows , 1998, Environ. Model. Softw..
[286] Hossein Bonakdari,et al. Stochastic model stationarization by eliminating the periodic term and its effect on time series prediction , 2017 .
[287] Ximing Cai,et al. Input variable selection for water resources systems using a modified minimum redundancy maximum relevance (mMRMR) algorithm , 2009 .
[288] A. I. McLeod,et al. Stochastic modelling of the effects of reservoir operation , 1977 .
[289] Felipe J. Colón-González,et al. Multimodel assessment of water scarcity under climate change , 2013, Proceedings of the National Academy of Sciences.
[290] S. Nazif,et al. Monthly prediction of streamflow using data-driven models , 2019, Journal of Earth System Science.
[291] C. Chatterjee,et al. Enhancing real-time streamflow forecasts with wavelet-neural network based error-updating schemes and ECMWF meteorological predictions in Variable Infiltration Capacity model , 2019, Journal of Hydrology.
[292] Asaad Y. Shamseldin,et al. Runoff forecasting using hybrid Wavelet Gene Expression Programming (WGEP) approach , 2015 .
[293] J. Adamowski. River flow forecasting using wavelet and cross‐wavelet transform models , 2008 .
[294] Zekâi Şen,et al. A mathematical model of monthly flow sequences / Un modèle mathématique des séquences débits mensuels , 1978 .
[295] Ashish Sharma,et al. A nonparametric approach for representing interannual dependence in monthly streamflow sequences , 2002 .
[296] Chao-Lin Chiu. Stochastic methods in hydraulics and hydrology of streamflow , 1972 .
[297] Aliasghar Montazar,et al. Sensitive analysis of optimized infiltration parameters in SWDC model , 2012 .