Partager

Recommandé par l'IIF / Document IIF

Un réseau neuronal artificiel avec méthode de contribution de groupe pour prédire le potentiel de réchauffement planétaire des frigorigènes et des composés apparentés à partir de leur structure moléculaire.

Prediction of global warming potentials of refrigerants and related compounds from their molecular structure – An artificial neural network with group contribution method.

Auteurs : DEVOTTA S., CHELANI A., VONSILD A.

Type d'article : Article de la RIF

Résumé

Global Warming Potentials (GWPs) of refrigerants and related compounds are calculated by complex simulation and periodically updated by World Meteorological Organisation (WMO). A new attempt has been made to predict GWPs of such compounds based on their molecular structure using Artificial Neural Network (ANN) and Group Contribution Method (GCM). The main focus is on refrigerants, including CFCs, HCFCs, HFCs, HFOs, HCs, chlorocarbons, fluorocarbons, bromocarbons, iodocarbons, oxygenated and unsaturated halocarbons. In order to give some statistical advantage to the ANN model, many other related families of compounds, totally about 495 compounds, have also been considered. Only GWPs for the time horizon of 100 years are used in this analysis. Considering the complexities of the problem and the confidence limits on GWP data published by WMO (2018), the proposed ANN with GCM model is able to predict the GWP within reasonable accuracy. A comparative analysis with another complex prediction method establishes the superiority of this direct GWP predictions from the molecular structure of a compound.

Documents disponibles

Format PDF

Pages : 756-765

Disponible

  • Prix public

    20 €

  • Prix membre*

    Gratuit

* meilleur tarif applicable selon le type d'adhésion (voir le détail des avantages des adhésions individuelles et collectives)

Détails

  • Titre original : Prediction of global warming potentials of refrigerants and related compounds from their molecular structure – An artificial neural network with group contribution method.
  • Identifiant de la fiche : 30029181
  • Langues : Anglais
  • Sujet : Environnement, Alternatives aux HFC
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 131
  • Date d'édition : 11/2021
  • DOI : http://dx.doi.org/10.1016/j.ijrefrig.2021.08.011
  • Document disponible en consultation à la bibliothèque du siège de l'IIF uniquement.

Liens


Voir d'autres articles du même numéro (95)
Voir la source

Indexation