Accéder directement au contenu Accéder directement à la navigation
Article dans une revue

A decision support system for eco-efficient biorefinery process comparison using a semantic approach

Abstract : Enzymatic hydrolysis of the main components of lignocellulosic biomass is one of the promising methods to further upgrading it into biofuels. Biomass pre-treatment is an essential step in order to reduce cellulose crystallinity, increase surface and porosity and separate the major constituents of biomass. Scientific literature in this domain is increasing fast and could be a valuable source of data. As these abundant scientific data are mostly in textual format and heterogeneously structured, using them to compute biomass pre-treatment efficiency is not straightforward. This paper presents the implementation of a Decision Support System (DSS) based on an original pipeline coupling knowledge engineering (KE) based on semantic web technologies, soft computing techniques and environmental factor computation. The DSS allows using data found in the literature to assess environmental sustainability of biorefinery systems. The pipeline permits to: (1) structure and integrate relevant experimental data, (2) assess data source reliability, (3) compute and visualize green indicators taking into account data imprecision and source reliability. This pipeline has been made possible thanks to innovative researches in the coupling of ontologies, uncertainty management and propagation. In this first version, data acquisition is done by experts and facilitated by a termino-ontological resource. Data source reliability assessment is based on domain knowledge and done by experts. The operational prototype has been used by field experts on a realistic use case (rice straw). The obtained results have validated the usefulness of the system. Further work will address the question of a higher automation level for data acquisition and data source reliability assessment.
Liste complète des métadonnées

Littérature citée [48 références]  Voir  Masquer  Télécharger

https://hal-lirmm.ccsd.cnrs.fr/lirmm-01346685
Déposant : Isabelle Gouat <>
Soumis le : jeudi 6 juin 2019 - 13:59:35
Dernière modification le : mardi 4 août 2020 - 11:24:02

Fichier

Lousteau-Cazalet_23723.pdf
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Charlotte Lousteau-Cazalet, Abdellatif Barakat, Jean-Pierre Belaud, Patrice Buche, Guillaume Busset, et al.. A decision support system for eco-efficient biorefinery process comparison using a semantic approach. Computers and Electronics in Agriculture, Elsevier, 2016, 127, pp.351-367. ⟨10.1016/j.compag.2016.06.020⟩. ⟨lirmm-01346685⟩

Partager

Métriques

Consultations de la notice

962

Téléchargements de fichiers

410