Neural Network Hydrological Modelling: An Evolutionary Approach-Reference-Cited by-同舟云学术

Neural Network Hydrological Modelling: An Evolutionary Approach

Published: Issue: Volume: Page:319-330
ISSN:0921-092X
Container-title:Practical Hydroinformatics
language:
Short-container-title:

Author:

Heppenstall A.J.,See L.M.,Abrahart R.J.,Dawson C.W.

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-79881-1_23.pdf

Reference22 articles.

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2. Abrahart, R.J., See, L.M., Heppenstall, A.J.: Neuroevolution applied to river level forecasting under winter flood and drought conditions. Journal of Intelligent Systems 16 (2007).

3. Dawson, C.W. Abrahart, R.J., See, L. HydroTest: a web-based toolbox of statistical measures for the standardised assessment of hydrological forecasts. Environmental Modelling and Software 27 (2007) 1034–1052.

4. Flake, G.W.: The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems and Adaptation. MIT Press, Cambridge MA, 4th edn. (2001).

5. Franchini, M.: Use of a Genetic Algorithm Combined with a Local Search Method for the Automatic Calibration of Conceptual Rainfall-runoff Models. Hydrological Sciences Journal. 41 (1996) 21–39.

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