Applying soft computing approaches to river level forecasting;L'utilisation de logiciels pour la prévision du niveau des rivières

Hydrological Sciences Journal

Volumn 44, Issue 5, 1999, Pages 763-778

  See, L ^a   Openshaw, S ^a  

^a UNIVERSITY OF LEEDS   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; FUZZY SETS; GENETIC ALGORITHMS; MATHEMATICAL MODELS; NEURAL NETWORKS; OPTIMIZATION; RIVERS;

HISTORICAL TIME SERIES DATA; RIVER CATCHMENT; RIVER LEVEL FORECASTING; SOFT COMPUTING;

FLOODS;

RIVER WATER;

EID: 0033381989     PISSN: 02626667     EISSN: 21503435     Source Type: Journal    
DOI: 10.1080/02626669909492272     Document Type: Article

References (35)

1. Abrahart, R. J., and Kneale, P. E., 1997. “ Exploring neural network rainfall-runoff modelling. ”. In Sixth National Hydrological Symposium (University of Salford, Manchester, UK, 15–18 September 1997), 9. 35–9.44. Institute of Hydrology, Wallingford, Oxfordshire, UK
2. Abrahart, R. J., and See, L., “ Neural network vs. ARMA modelling:constructing benchmark case studies of river flow prediction. ”. In Hydrol. Processes. (in press)
3. Bárdossy, A., and Disse, M., 1993. Fuzzy rule-based models for infiltration. Wat. Resour. Res., 29:373–382.
4. Box, G. E. P., and Jenkins, G. M., 1976. Time Series Analysis:Forecasting and Control. Oakland.:Holden-Day.
5. Cordón, O., and Herrera, F., 1995. “ A general study on genetic fuzzy systems. ”. In Genetic Algorithms in Engineering and Computer Science Edited by:Winter, G., Pénaux, J., Galǎn, M., and Cuesta, P., 33–57. Chichester. West Sussex, UK:John Wiley & Sons.
6. Dawson, C. W., and Wilby, R. E., 1998. An artificial neural network approach to rainfall-runoff modelling. Hydrol. Set J., 43 (1):47–66.
7. Environment Agency. 1996a. State of the Environment. UK:Environment Agency. http://www.environmentagency.gov.uk.
8. Environment Agency. 1996b. North East Region Flood Warning Manual Part I. Leeds, UK:Environment Agency.
9. Fortin, V., Ouarda, T. B.M.J., and Bobée, B., 1997. Wat Resour. Res. Edited by:Maier, H. R., and Dandy, G. C., Vol. 33, 2423–2424. Comment on “The use of artificial neural networks for the prediction of water quality parameters”(ed. by
10. Franchini, M., 1996. Use of a genetic algorithm combined with a local search method for the automatic calibration of conceptual rainfall-runoff models. Hydrol. Sci. J., 41 (1):21–39.
11. Franchini, M., and Galeati, G., 1997. Comparing several genetic algorithm schemes for the calibration of conceptual rainfall-runoff models. Hydrol. Sci. J., 42 (3):357–380.
12. Franchini, M., Galeati, G., and Berra, S., 1998. Global optimization techniques for the calibration of conceptual rainfall-runoff models. Hydrol. Sci. J., 43 (3):443–458.
13. Goldberg, D., 1989. Genetic Algorithms in Search, Optimization and Machine Learning. Reading, Massachusetts, USA:Addison-Wesley.
14. Holland, J., 1975. Adaptation in Natural and Artificial Systems. Cambridge, Massachusetts, USA:MIT Press.
15. Jang, J.-S. R., Sun, C.-T., and Mizutani, E., 1997. Neuro-Fuzzy and Soft Computing. New Jersey, USA:Prentice Hall.
16. Karr, C. L., 1991. Genetic algorithms for fuzzy logic controllers. AI Expert, 6:26–33.
17. Kasabov, N. K., 1996. Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering. Cambridge, Massachusetts, USA:MIT Press.
18. Kohonen, T., 1984. Self-Organization and Associative Memory. Berlin, Germany.:Springer-Verlag.
19. Kosko, B., 1992. Neural Networks and Fuzzy Systems:A Dynamical Systems Approach to Machine Intelligence. New Jersey, USA:Prentice Hall.
20. Kosko, B., 1997. Fuzzy Engineering. London, UK:Prentice Hall.
21. Lin, C. T., and Lee, C. S. G., 1996. Neural Fuzzy Systems:A Neuro-Fuzzy Synergism to Intelligent Systems. New Jersey, USA:Prentice Hall PTR, Upper Saddle River.
22. Minns, A. W., and Hall, M. J., 1996. Artificial neutral networks as rainfall-runoff models. Hydrol. Sci. J., 41 (3):399–417.
23. Moore, R. J., Jones, D. A., Black, K. B., Austin, R. M., Carrington, D. S., Tinnion, M., and Akhondi, A., 1994. “ RFFS and HYRAD:integrated systems for rainfall and river flow forecasting in real-time and their application in Yorkshire. ”. In BHS Occasional Paper no. 4, British Hydrological Society.
24. Rumelhart, D. E., Hinton, G. E., and Williams, R. J., 1986. “ Learning internal representation by error propagation. ”. In Parallel Distributed Processing:Explorations in the Microstructure of Cognition Edited by:Rumelhart, D. E., and McClelland, J. L., 318–362. Cambridge, Massachusetts, USA:MIT Press.
25. See, L., and Openshaw, S., 1998. “ Using soft computing techniques to enhance flood forecasting on the River Ouse. ”. In Proc. Hydroinformatics 98 Edited by:Babovic, V., and Larsen, L. C., 819–824. Rotterdam, The Netherlands.:Balkema.
26. See, L., Corne, S., Dougherty, M., and Openshaw, S., 1997. “ Some initial experiments with neural network models of flood forecasting on the River Ouse. ”. In Proc. Second Int. Conf. on GeoComputation (University of Otago, Dunedin, New Zealand, 26–29 August 1997) Edited by:Pascoe, R. T., 59–67. Dunedin, New Zealand.:Spatial Information Research Centre, Univ. Otago.
27. Smith, J., and Eli, R. N., 1995. Neural-network models of rainfall-runoff process. J. Wat. Resour. Plan. Manage., 121:499–509.
28. Sugeno, M., and Kang, G. T., 1988. Structure identification of fuzzy model. Fuzzy Sets Syst., 28:15–33.
29. Takagi, T., and Sugeno, M., 1985. Fuzzy identification of systems and its application to modelling and control. IEEE Trans. Systems, Man and Cybernetics, 15:116–132.
30. University of Stuttgart. 1998. Stuttgart Neural Network Simulator. Stuttgart, Germany:Institute of Parallel and Distributed High-Performance Systems. http://www-ra.informatik.uni-tuebingert.de/SNNS/.
31. van der Voort, M., Dougherty, M., and Watson, S., 1996. Combining Kohonen maps with ARIMA time series models to forecast traffic flow. Transportation Research Part C-Emerging Technologies, 4:307–318.
32. Wang, L., 1994. Adaptive Fuzzy Systems and Control:Design and Stability Analysis. Englewood Cliffs, New Jersey, USA:Prentice Hall PTR.
33. Wang, Q. J., 1991. The genetic algorithm and its application to calibration of conceptual rainfall-runoff models. Wat. Resour. Res., 27:2467–2471.
34. Zadeh, L., 1965. Fuzzy sets. Information and Control, 8:338–353.
35. Zadeh, L., 1994. Soft computing and fuzzy logic. IEEE Software, 11:48–56.