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Autores
Categoria WoS
Area
  • Applications
  • Artificial Neural Networks
  • Genetic Programming
Titulo: Prediction and Modelling of the Rainfall-Runoff Transformation of a Typical Urban Basin Using ANN and GP
Tipo: revista internacional
Fecha: 4,2003
Revista: Applied Artificial Intelligence
JCR Journal; Impact Factor: 0.789
SCIMago SJR:
Citas ISI: 10 Citas Scopus: 14 Citas Google Scholar: 17
Volumen: 17(4)
Paginas: 329-343
ISSN: 0883-9514
Editorial: Taylor & Francis
Berlin (Alemania)

Abstract:

This paper proposes an application of Genetic Programming (GP) and Artificial Neural Networks (ANN) in hydrology, showing how these two techniques can work together to solve a problem, namely for modeling the effect of rain on the runoff folw in a typical urban basin. The ultimate goal of this research is to desing a real-time alarm system to warn of floods or subsidence in various types of urban basin. Results look promising and appear to offer some improvement for analyzing river basin system over stochastic methods such as unitary hydrographs.

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