Machine Learning and Its Application to Reacting Flows ML and Combustion /

Machine Learning and Its Application to Reacting Flows ML and Combustion /

Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Swaminathan, Nedunchezhian (Editor), Parente, Alessandro (Editor)
Summary:XI, 346 p. 127 illus., 98 illus. in color.
text
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:Lecture Notes in Energy, 44
Subjects:
Cogeneration of electric power and heat.
Fossil fuels.
Thermodynamics.
Heat engineering.
Heat transfer.
Mass transfer.
Machine learning.
Fossil Fuel.
Engineering Thermodynamics, Heat and Mass Transfer.
Machine Learning.
Online Access:https://doi.org/10.1007/978-3-031-16248-0
Format: Electronic Book

Internet

https://doi.org/10.1007/978-3-031-16248-0

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