Comparison of multilayer perceptron and radial basis function networks as tools for flood forecasting

IAHS-AISH Publication

Volumn , Issue 239, 1997, Pages 173-181

  Jayawardena, A W ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 27844470296     PISSN: 01447815     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (6)

1. Bianchini, M., Frasconi, P. & Gori, M. (1995) Learning without local minima in radial basis function networks. IEEE Trans. Neural Networks 6(3), 749-755.
2. Chen, S., Cowan, C. F. N. & Grant, P. M. (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans. Neural Networks 2(2), 302-309.
3. Isobe, I., Ohkado, T., Hanyuda, H., Oda, S. & Gotoh, Y. (1994) The development of a forecasting system of the water levels of rivers by neural networks (in Japanese). J. Japan Soc. Hydrol. & Wat. Res. 7(2), 90-97.
4. Jayawardena, A. W. & Fernando, D. A. K. (1995) Hydrologjcal forecasting using artificial neural networks. In Proc. Second Int. Study Conf. on GEWEX in Asia and GAME (Thailand), 376-379.
5. Jayawardena, A. W. & Fernando, D. A. K. (1995) Artificial neural networks in hydrometeorological modelling. In: Proc. Fourth Int. Conf. on the Application of Artificial Intelligence to Civil and Structural Engineering (eu. by B. H. V. Topping) (Cambridge, UK), 115-120. Civil Comp Press.
6. Liong, S. Y. & Chan, W. T. (1993) Runoff volume estimates with neural networks. In: Proc. Third International Conf. in the Application of Artificial Intelligence to Civil and Structural Engineering (ed. by B. H. V. Topping & A. I. Khan) (Edinburgh, UK), 67-70. Civil Comp Press.