Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)

Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)

The paper introduces the artificial intelligence (AI) approach for modeling fluidized adsorption beds. The idea of fluidized bed application allows a significantly increased heat transfer coefficient between adsorption bed and the surface of a heat exchanger, improving the performance of adsorption...

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Bibliographic Details
Main Authors: Dorian Skrobek, Jaroslaw Krzywanski, Marcin Sosnowski, Anna Kulakowska, Anna Zylka, Karolina Grabowska, Katarzyna Ciesielska, Wojciech Nowak
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Energies
Subjects:
sorption processes
deep learning
neural networks
Long Short-Term Memory (LSTM)
Online Access:https://www.mdpi.com/1996-1073/13/24/6601

Internet

https://www.mdpi.com/1996-1073/13/24/6601

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