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Eric Duviella

Researcher at university of lille

Publications -  110
Citations -  930

Eric Duviella is an academic researcher from university of lille. The author has contributed to research in topics: Inland navigation & Fault detection and isolation. The author has an hindex of 13, co-authored 100 publications receiving 748 citations. Previous affiliations of Eric Duviella include Institut Mines-Télécom & École des Mines de Douai.

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A recursive identification algorithm for switched linear/affine models

TL;DR: It has been observed that by appropriately choosing the data assignment criterion, the proposed on-line method can be extended to deal also with the identification of piecewise affine models and is tested through some computer simulations and the modeling of an open channel system.
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Leak localization in water distribution networks using a mixed model-based/data-driven approach

TL;DR: In this paper, a new method for leak localization in water distribution networks (WDNs) is proposed, where residuals are obtained by comparing pressure measurements with the estimations provided by a WDN model, and a classifier is applied to the residuals with the aim of determining the leak location.
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Leak Localization in Water Distribution Networks using Pressure Residuals and Classifiers

TL;DR: A data-driven approach based on the use of statistical classifiers working in the residual space is proposed for leak localization, trained using leak data scenarios in all the nodes of the network considering uncertainty in demand distribution, additive noise in sensors and leak magnitude.
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Data-driven modeling for river flood forecasting based on a piecewise linear ARX system identification

TL;DR: This paper gives an alternative approach to the existing rainfall/runoff linear and nonlinear models by the utilization of a hybrid system consisting in a Piecewise Auto-Regressive eXogeneous (PWARX) structure identified using an approach that alternates between data assignment and parameter estimation.
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Model predictive control and moving horizon estimation for water level regulation in inland waterways

TL;DR: The results show that the proposed methodology is able to guarantee the navigability condition, as well as the other operational goals.