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Sanitary risk detection for a safer food chain management

Abstract : Nowadays, several risk-attitude elicitation techniques are applied in order to guarantee the highest levels of safety and quality control in the food chain. Here we explore an approach to the risk measurement problem of any multiparameter production framework using precise decision making tools. The application model of artificial neural networks is presented in order to determine the global risk related to a given production. The proposed tool uses a feed-forward network able to treat any set of nonlinearly separable production markers. The risk values obtained with this approach are incorporated into the expedition management system in order to perform smarter deliveries and more accurate sanitary controls.
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Submitted on : Friday, June 17, 2011 - 12:40:07 PM
Last modification on : Friday, February 4, 2022 - 3:17:56 AM


  • HAL Id : inria-00601312, version 1


Simon Tamayo, Thibaud Monteiro, Nathalie Sauer. Sanitary risk detection for a safer food chain management. Third International Conference on Information Systems, Logistics and Supply Chain - ILS 2010, Apr 2010, Casablanca, Morocco. ⟨inria-00601312⟩



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