Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques

[1]  Karl Pearson F.R.S. LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[2]  H. Hotelling Analysis of a complex of statistical variables into principal components. , 1933 .

[3]  N. Draper,et al.  Applied Regression Analysis. , 1967 .

[4]  P. E. O'connell,et al.  River flow forecasting through conceptual models part III - The Ray catchment at Grendon Underwood , 1970 .

[5]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[6]  J. Scott Armstrong,et al.  Long-Range Forecasting. , 1979 .

[7]  J. ...,et al.  Applied modeling of hydrologic time series , 1980 .

[8]  P. Kitanidis,et al.  Real‐time forecasting with a conceptual hydrologic model: 2. Applications and results , 1980 .

[9]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.

[10]  W. Hays Applied Regression Analysis. 2nd ed. , 1981 .

[11]  A. Gilchrist,et al.  Long‐range forecasting , 1986 .

[12]  Fraser,et al.  Independent coordinates for strange attractors from mutual information. , 1986, Physical review. A, General physics.

[13]  Theiler,et al.  Spurious dimension from correlation algorithms applied to limited time-series data. , 1986, Physical review. A, General physics.

[14]  Robert Sandy,et al.  Statistics for Business and Economics , 1989 .

[15]  George Sugihara,et al.  Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series , 1990, Nature.

[16]  John R. Koza,et al.  Genetic Programming II , 1992 .

[17]  H. Abarbanel,et al.  Determining embedding dimension for phase-space reconstruction using a geometrical construction. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[18]  Soung Hie Kim,et al.  An Artificial Neural Network Approach , 1993 .

[19]  Cheng-Few Lee,et al.  Statistics For Business And Financial Economics , 1993 .

[20]  Yuxiang He,et al.  Long‐range prediction of hawaiian winter rainfall using canonical correlation analysis , 1994 .

[21]  A. Jayawardena,et al.  Analysis and prediction of chaos in rainfall and stream flow time series , 1994 .

[22]  D. M. Titterington,et al.  Neural Networks: A Review from a Statistical Perspective , 1994 .

[23]  Philippe De Wilde Neural Network Models , 1996 .

[24]  R. McCuen Hydrologic Analysis and Design , 1997 .

[25]  A. Shamseldin,et al.  Methods for combining the outputs of different rainfall–runoff models , 1997 .

[26]  Taha B. M. J. Ouarda,et al.  Comment on “The use of artificial neural networks for the prediction of water quality parameters” by H. R. Maier and G. C. Dandy , 1997 .

[27]  Sanjeev S. Tambe,et al.  Prediction of all India summer monsoon rainfall using error-back-propagation neural networks , 1997 .

[28]  D. Legates,et al.  Evaluating the use of “goodness‐of‐fit” Measures in hydrologic and hydroclimatic model validation , 1999 .

[29]  A. Shamseldin,et al.  A real-time combination method for the outputs of different rainfall-runoff models , 1999 .

[30]  Johnny C. L. Chan,et al.  Prediction of the summer monsoon rainfall over South China , 1999 .

[31]  Rao S. Govindaraju,et al.  Prediction of watershed runoff using Bayesian concepts and modular neural networks , 2000 .

[32]  Stan Openshaw,et al.  A hybrid multi-model approach to river level forecasting , 2000 .

[33]  George H. Leavesley,et al.  Prediction of a Flash Flood in Complex Terrain. Part II: A Comparison of Flood Discharge Simulations Using Rainfall Input from Radar, a Dynamic Model, and an Automated Algorithmic System , 2000 .

[34]  John A. Dracup,et al.  Artificial Neural Networks and Long-Range Precipitation Prediction in California , 2000 .

[35]  Dingli Yu,et al.  Neural model input selection for a MIMO chemical process , 2000 .

[36]  E. Toth,et al.  Comparison of short-term rainfall prediction models for real-time flood forecasting , 2000 .

[37]  Tiesong Hu,et al.  River flow time series prediction with a range-dependent neural network , 2001 .

[38]  Shie-Yui Liong,et al.  Rainfall and runoff forecasting with SSA-SVM approach , 2001 .

[39]  Istvan Bogardi,et al.  Fuzzy rule-based prediction of monthly precipitation , 2001 .

[40]  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 .

[41]  K. Lam,et al.  River flow time series prediction with a range-dependent neural network , 2001 .

[42]  Christian W. Dawson,et al.  Hydrological modelling using artificial neural networks , 2001 .

[43]  Robert J. Abrahart,et al.  Multi-model data fusion for river flow forecasting: an evaluation of six alternative methods based on two contrasting catchments , 2002 .

[44]  Andrew L. Rukhin,et al.  Analysis of Time Series Structure SSA and Related Techniques , 2002, Technometrics.

[45]  Armando Brath,et al.  Neural networks and non-parametric methods for improving real-time flood forecasting through conceptual hydrological models , 2002 .

[46]  Kuolin Hsu,et al.  Self‐organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis , 2002 .

[47]  Timothy DelSole,et al.  Linear Prediction of Indian Monsoon Rainfall , 2002 .

[48]  K. P. Sudheer,et al.  A data‐driven algorithm for constructing artificial neural network rainfall‐runoff models , 2002 .

[49]  U. C. Kothyari,et al.  Artificial neural networks for daily rainfall—runoff modelling , 2002 .

[50]  Alessandra Fanni,et al.  Neural network models to forecast hydrological risk , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

[51]  A. Soldati,et al.  Artificial neural network approach to flood forecasting in the River Arno , 2003 .

[52]  Auroop R. Ganguly,et al.  Distributed Quantitative Precipitation Forecasting Using Information from Radar and Numerical Weather Prediction Models , 2003 .

[53]  Francesco Masulli,et al.  Application of an ensemble technique based on singular spectrum analysis to daily rainfall forecasting , 2003, Neural Networks.

[54]  Dimitri P. Solomatine,et al.  M5 Model Trees and Neural Networks: Application to Flood Forecasting in the Upper Reach of the Huai River in China , 2004 .

[55]  Gwo-Fong Lin,et al.  Application of an artificial neural network to typhoon rainfall forecasting , 2022 .

[56]  T. Rientjes,et al.  Constraints of artificial neural networks for rainfall-runoff modelling: trade-offs in hydrological state representation and model evaluation , 2005 .

[57]  Paulin Coulibaly,et al.  Improving Daily Reservoir Inflow Forecasts with Model Combination , 2005 .

[58]  Shie-Yui Liong,et al.  Flow categorization model for improving forecasting , 2005 .

[59]  Marco Sandri,et al.  Combining Singular-Spectrum Analysis and neural networks for time series forecasting , 2005, Neural Processing Letters.

[60]  J. A. Ferreira,et al.  Singular spectrum analysis and forecasting of hydrological time series , 2006 .

[61]  Durga L. Shrestha,et al.  Machine learning approaches for estimation of prediction interval for the model output , 2006, Neural Networks.

[62]  P. Gelder,et al.  Forecasting daily streamflow using hybrid ANN models , 2006 .

[63]  Ashu Jain,et al.  Integrated approach to model decomposed flow hydrograph using artificial neural network and conceptual techniques , 2006 .

[64]  Ming Xue,et al.  Short-range prediction of a heavy precipitation event by assimilating Chinese CINRAD-SA radar reflectivity data using complex cloud analysis , 2006 .

[65]  Taesoon Kim,et al.  Multireservoir system optimization in the Han River basin using multi‐objective genetic algorithms , 2006 .

[66]  D. Savić,et al.  A symbolic data-driven technique based on evolutionary polynomial regression , 2006 .

[67]  C. Sivapragasam,et al.  Genetic programming model for forecast of short and noisy data , 2007 .

[68]  T. Hu,et al.  Rainfall–runoff modeling using principal component analysis and neural network , 2007 .

[69]  O. Kisi,et al.  Wavelet and neuro-fuzzy conjunction model for precipitation forecasting , 2007 .

[70]  Dimitri P. Solomatine,et al.  Baseflow separation techniques for modular artificial neural network modelling in flow forecasting , 2007 .

[71]  K. K. Kumar,et al.  Long range prediction of Indian summer monsoon rainfall , 2007 .

[72]  Avi Ostfeld,et al.  Data-driven modelling: some past experiences and new approaches , 2008 .

[73]  Holger R. Maier,et al.  Non-linear variable selection for artificial neural networks using partial mutual information , 2008, Environ. Model. Softw..

[74]  K. W. Chau,et al.  River stage prediction based on a distributed support vector regression , 2008 .

[75]  Rajesh Janardanan,et al.  An empirical model for the seasonal prediction of southwest monsoon rainfall over Kerala, a meteorological subdivision of India , 2008 .

[76]  Surajit Chattopadhyay,et al.  Identification of the best hidden layer size for three-layered neural net in predicting monsoon rainfall in India , 2008 .

[77]  Qingcun Zeng,et al.  Statistical Prediction of East Asian Summer Monsoon Rainfall Based on SST and Sea Ice Concentration , 2008 .

[78]  P. Malguzzi,et al.  Discharge prediction based on multi-model precipitation forecasts , 2008 .

[79]  P. Guhathakurta,et al.  Long lead monsoon rainfall prediction for meteorological sub-divisions of India using deterministic artificial neural network model , 2008 .

[80]  Gwo-Fong Lin,et al.  A hybrid neural network model for typhoon-rainfall forecasting , 2009 .

[81]  Gwo-Fong Lin,et al.  Effective forecasting of hourly typhoon rainfall using support vector machines , 2009 .

[82]  C. L. Wu,et al.  Methods to improve neural network performance in daily flows prediction , 2009 .

[83]  Kurt Hornik,et al.  Neural Network Models , 2011 .