A hybrid neural network model for typhoon-rainfall forecasting

Journal of Hydrology

Volumn 375, Issue 3-4, 2009, Pages 450-458

  Lin, Gwo Fong ^a   Wu, Ming Chang ^a  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Hybrid neural network; Multilayer perceptron network; Self organizing map; Typhoon rainfall forecasting

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DATA ANALYSIS TECHNIQUES; DISCRIMINATION ANALYSIS; FORECASTING PERFORMANCE; HYBRID NEURAL NETWORK; HYBRID NEURAL NETWORKS; INPUT AND OUTPUTS; INPUT DATAS; MULTI-LAYER PERCEPTRON NETWORKS; MULTILAYER PERCEPTRON NETWORK; MULTIVARIATE NON-LINEAR REGRESSION; NONLINEAR REGRESSION TECHNIQUE; ONE STEP; RAINFALL FORECASTING; SELF-ORGANIZING MAP; TANSHUI RIVER BASIN; TOPOLOGICAL RELATIONSHIPS; TYPHOON RAINFALL; TYPHOON-RAINFALL FORECASTING;

CLUSTER ANALYSIS; CONFORMAL MAPPING; ELECTRIC LOADS; FORECASTING; HURRICANES; INPUT OUTPUT PROGRAMS; MULTILAYERS; STRENGTH OF MATERIALS;

MULTILAYER NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; CLIMATE MODELING; CLUSTER ANALYSIS; DISCRIMINANT ANALYSIS; MULTIVARIATE ANALYSIS; NONLINEARITY; RAINFALL; REGRESSION ANALYSIS; RIVER BASIN; TYPHOON; WEATHER FORECASTING;

ASIA; EURASIA; FAR EAST; TAIWAN; TANSHUI RIVER;

EID: 69349084510     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2009.06.047     Document Type: Article

References (28)

1. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology. Artificial neural networks in hydrology I: preliminary concepts. Journal of Hydrologic Engineering 5 2 (2000) 115-123
2. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology. Artificial neural networks in hydrology II: hydrologic applications. Journal of Hydrologic Engineering 5 2 (2000) 124-137
3. Bowden G.J., Dandy G.C., and Maier H.R. Input determination for neural network models in water resources applications: part 1 - background and methodology. Journal of Hydrology 301 1-4 (2005) 75-92
4. French M.N., Krajewski W.F., and Cuykendall R.R. Rainfall forecasting in space and time using a neural network. Journal of Hydrology 137 1-4 (1992) 1-31
5. Govindaraju R.S., and Rao A.R. Artificial Neural Networks in Hydrology (2000), Kluwer, The Netherlands
6. Haykin S. Neural Networks: A Comprehensive Foundation (1999), Prentice Hall, New Jersey
7. Hsu K.L., Gupta H.V., Gao X., Sorooshian S., and Imam B. Self-organizing linear output map (SOLO): an artificial neural network suitable for hydrologic modeling and analysis. Water Resources Research 38 12 (2002) 10-26
8. Kitanidis P.K. Geostatistics. In: Maidment D.R. (Ed). Handbook of Hydrology (1993), McGraw-Hill, New York 20.1-20.39
9. Kohonen T. Self-organizing Maps (2001), New York, Springer
10. Lin G.F., and Chen G.R. A systematic approach to the input determination for neural network rainfall-runoff models. Hydrological Processes 22 14 (2008) 2524-2530
11. Lin G.F., and Chen L.H. A non-linear rainfall-runoff model using radial basis function network. Journal of Hydrology 289 1-4 (2004) 1-8
12. Lin G.F., and Chen L.H. A spatial interpolation method based on radial basis function networks incorporating a semivariogram model. Journal of Hydrology 288 3-4 (2004) 288-298
13. Lin G.F., and Chen L.H. Application of an artificial neural network to typhoon rainfall forecasting. Hydrological Processes 19 9 (2005) 1825-1837
14. Lin G.F., and Chen L.H. Time series forecasting by combining the radial basis function network and the self-organizing map. Hydrological Processes 19 10 (2005) 1925-1937
15. Lin G.F., and Chen L.H. Identification of homogeneous regions for regional frequency analysis using the self-organizing map. Journal of Hydrology 324 1-4 (2006) 1-9
16. Lin G.F., and Wang C.M. Performing cluster analysis and discrimination analysis of hydrological factors in one step. Advances in Water Resources 29 11 (2006) 1573-1585
17. Lin G.F., and Wu M.C. A SOM-based approach to estimating design hyetographs of ungauged sites. Journal of Hydrology 339 3-4 (2007) 216-226
18. Luk K.C., Ball J.E., and Sharma A. A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting. Journal of Hydrology 227 (2000) 56-65
19. Luk K.C., Ball J.E., and Sharma A. An application of artificial neural networks for rainfall forecasting. Mathematical and Computer Modelling 33 6-7 (2001) 683-693
20. Mangiameli P., Chen S.K., and West D. A comparison of SOM neural network and hierarchical clustering methods. European Journal of Operational Research 93 (1996) 402-417
21. Michaelides S.C., Pattichis C.S., and Kleovoulou G. Classification of rainfall variability by using artificial neural networks. International Journal of Climatology 21 (2001) 1401-1414
22. Muttil N., and Chau K.W. Neural network and genetic programming for modelling coastal algal blooms. International Journal of Environment and Pollution 28 3-4 (2006) 223-238
23. Nash J.E., and Sutcliffe J.V. River flow forecasting through conceptual models. Part 1: a discussion of principles. Journal of Hydrology 10 3 (1970) 282-290
24. Ramirez M.C.V., Velho H.F.D., and Ferreira N.J. Artificial neural network technique for rainfall forecasting applied to the Sao Paulo region. Journal of Hydrology 301 1-4 (2005) 146-162
25. Partal T., and Cigizoglu H.K. Estimation and forecasting of daily suspended sediment data using wavelet-neural networks. Journal of Hydrology 358 3-4 (2008) 317-331
26. Pulido-Calvo I., and Portela M.M. Application of neural approaches to one-step daily flow forecasting in Portuguese watersheds. Journal of Hydrology 332 1-2 (2007) 1-15
27. Wu C.L., and Chau K.W. A flood forecasting neural network model with genetic algorithm. International Journal of Environment and Pollution 28 3-4 (2006) 261-273
28. Xie J.X., Cheng C.T., Chau K.W., and Pei Y.Z. A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity. International Journal of Environment and Pollution 28 3-4 (2006) 364-381