The Monte Carlo driven and machine learning enhanced process simulator-Reference-Cited by-同舟云学术

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The Monte Carlo driven and machine learning enhanced process simulator

Published:2019-06 Issue: Volume:125 Page:324-338
ISSN:0098-1354
Container-title:Computers & Chemical Engineering
language:en
Short-container-title:Computers & Chemical Engineering

Author:

Jones Mark Nicholas,Frutiger Jérôme,Ince Nevin Gerek,Sin Gürkan

Funder

European Union’s Horizon 2020 Research and Innovation Programme

Publisher

Elsevier BV

Subject

Computer Science Applications,General Chemical Engineering

Reference55 articles.

1. On spectral methods for variance based sensitivity analysis;Alexanderian;Probab. Surveys,2013

2. An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis;Blatman;Probab. Eng. Mech.,2010

3. New group contribution method for estimating properties of pure compounds;Constantinou;AlChE J.,1994

4. Computer-Aided Modeling of Lipid Processing Technology;Diaz Tovar,2011

5. Thermodata engine (tde): software implementation of the dynamic data evaluation concept. 8. properties of material streams and solvent design;Diky;J. Chem. Inf. Model,2013

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