Modelling non Measurable Processes by Neural Networks: Forecasting Underground Flow Case Study of the Céze Basin (Gard - France)
A Johannet, PA Ayral, B Vayssade - Advances and Innovations in Systems …, 2007 - Springer
A Johannet, PA Ayral, B Vayssade
Advances and Innovations in Systems, computing sciences and software engineering, 2007•SpringerAfter a presentation of the nonlinear properties of neural networks, their applications to
hydrology are described. A neural predictor is satisfactorily used to estimate a flood peak.
The main contribution of the paper concerns an original method for visualising a hidden
underground flow Satisfactory experimental results were obtained that fitted well with the
knowledge of local hydrogeology, opening up an interesting avenue for modelling using
neural networks.
hydrology are described. A neural predictor is satisfactorily used to estimate a flood peak.
The main contribution of the paper concerns an original method for visualising a hidden
underground flow Satisfactory experimental results were obtained that fitted well with the
knowledge of local hydrogeology, opening up an interesting avenue for modelling using
neural networks.
Abstract
After a presentation of the nonlinear properties of neural networks, their applications to hydrology are described. A neural predictor is satisfactorily used to estimate a flood peak. The main contribution of the paper concerns an original method for visualising a hidden underground flow Satisfactory experimental results were obtained that fitted well with the knowledge of local hydrogeology, opening up an interesting avenue for modelling using neural networks.
Springer
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