Accounts of Experiences in the Application of Artificial Neural Networks in Chemical Engineering

2008 ◽  
Vol 47 (16) ◽  
pp. 5782-5796 ◽  
Author(s):  
David M. Himmelblau
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Chemical Engineering ◽  
Artificial Neural

Experimental methods in chemical engineering: Artificial neural networks–ANNs

2019 ◽  
Vol 97 (9) ◽  
pp. 2372-2382 ◽  
Author(s):  
Jacopo Panerati ◽  
Matthias A. Schnellmann ◽  
Christian Patience ◽  
Giovanni Beltrame ◽  
Gregory S. Patience
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Chemical Engineering ◽  
Experimental Methods ◽  
Artificial Neural

scholarly journals Artificial Neural Networks for Pyrolysis, Thermal Analysis, and Thermokinetic Studies: The Status Quo

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3727
Author(s):  
Nikita V. Muravyev ◽  
Giorgio Luciano ◽  
Heitor Luiz Ornaghi ◽  
Roman Svoboda ◽  
Sergey Vyazovkin
Keyword(s):  
Neural Networks ◽  
Thermal Analysis ◽  
Artificial Neural Networks ◽  
Chemical Engineering ◽  
Model Fitting ◽  
Research Areas ◽  
The Status ◽  
Nonlinear Trends ◽  
Artificial Neural ◽  
Critical Overview

Artificial neural networks (ANNs) are a method of machine learning (ML) that is now widely used in physics, chemistry, and material science. ANN can learn from data to identify nonlinear trends and give accurate predictions. ML methods, and ANNs in particular, have already demonstrated their worth in solving various chemical engineering problems, but applications in pyrolysis, thermal analysis, and, especially, thermokinetic studies are still in an initiatory stage. The present article gives a critical overview and summary of the available literature on applying ANNs in the field of pyrolysis, thermal analysis, and thermokinetic studies. More than 100 papers from these research areas are surveyed. Some approaches from the broad field of chemical engineering are discussed as the venues for possible transfer to the field of pyrolysis and thermal analysis studies in general. It is stressed that the current thermokinetic applications of ANNs are yet to evolve significantly to reach the capabilities of the existing isoconversional and model-fitting methods.

Artificial neural networks: applications in chemical engineering

2013 ◽  
Vol 29 (4) ◽  
Author(s):  
Mohsen Pirdashti ◽  
Silvia Curteanu ◽  
Mehrdad Hashemi Kamangar ◽  
Mimi H. Hassim ◽  
Mohammad Amin Khatami
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Chemical Engineering ◽  
Artificial Neural

FUTURE OF ARTIFICIAL NEURAL NETWORKS IN SPACE EXPLORATION AND SPACE ENGINEERING

2018 ◽  
pp. 6-11
Author(s):  
Kobiljon Kh. Zoidov ◽  
◽  
Svetlana V. Ponomareva ◽  
Daniel I. Serebryansky ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Space Exploration ◽  
Artificial Neural
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