Didier Graillot

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Abstrad-The paper presents the development of a real-time expert system (RTES) for supervision and fault detection in urban drainage systems (UDS). Several vita1 characteristics of such an expert tool, in which the project is being developed, are recalled. The main aspects of the modelling of the UDS and the detection of faults are outlined and illustrated(More)
  • Shishir Gaur, Sudheer Ch, Didier Graillot, B R Chahar, D Nagesh Kumar, S Gaur +4 others
  • 2013
Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN)(More)
Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward(More)
Future climate changes and the resulting modifications in anthropogenic activities will alter the interactions between rivers and groundwater. The quantification of these hydraulic interactions is absolutely necessary for achieving sustainable water use and requires accurate analytical methodologies. This report proposes an interdisciplinary approach to the(More)
The use of neural networks is still difficult in many application areas due to the lack of explanation facilities (the « black box » problem). An example of such applications is multiple criteria decision making (MCDM), applied to location problems having environmental impact. However, the concepts and methods presented are also applicable to other problem(More)
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