Documents disponibles écrits par cet auteur

Sustainability assessment of industrial systems under uncertainty / Cristina Piluso in Industrial & engineering chemistry research, Vol. 49 N° 18 (Septembre 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 18 (Septembre 2010) . - pp. 8633–8643 Titre : Sustainability assessment of industrial systems under uncertainty : a fuzzy logic based approach to short-term to midterm predictions Type de document : texte imprimé Auteurs : Cristina Piluso, Auteur ; Jennifer Huang, Auteur ; Zheng Liu, Auteur Année de publication : 2010 Article en page(s) : pp. 8633–8643 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Industrial  Systems Résumé : The sustainability assessment of industrial systems is always a very challenging task due to the existence of various types of uncertainties that are associated with the available data, assessable information, possessed knowledge, and problem understanding, etc. This paper introduces a fuzzy logic based approach for the effective short- and long-term assessment of industrial sustainability under the restrictions of aleatory and epistemic uncertainties. A comprehensive study on a metal-finishing-centered industrial zone is illustrated to show the efficacy of the introduced methodology. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie100164r [article] Sustainability assessment of industrial systems under uncertainty : a fuzzy logic based approach to short-term to midterm predictions [texte imprimé] / Cristina Piluso, Auteur ; Jennifer Huang, Auteur ; Zheng Liu, Auteur . - 2010 . - pp. 8633–8643. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 18 (Septembre 2010) . - pp. 8633–8643 Mots-clés : Industrial  Systems Résumé : The sustainability assessment of industrial systems is always a very challenging task due to the existence of various types of uncertainties that are associated with the available data, assessable information, possessed knowledge, and problem understanding, etc. This paper introduces a fuzzy logic based approach for the effective short- and long-term assessment of industrial sustainability under the restrictions of aleatory and epistemic uncertainties. A comprehensive study on a metal-finishing-centered industrial zone is illustrated to show the efficacy of the introduced methodology. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie100164r