Advanced Digital, Modeling and Control Applies into Various Processes

doi:10.3390/books978-3-7258-1425-1

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Hardback

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Keywords

digital signal processing; control systems; smart grids; Internet of things; flexible ac transmission systems; big data; rolling mill; rolled steel; rolling mill roll wear; mathematical model; correlation coefficient; DEM; discrete element method; calibration; ore; universal approach; experiment; friction; friction coefficients; DEM parameters; computer vision; synthetic data; steel defect detection; machine learning; axisymmetric parts; optical control; control of geometric parameters; method with spatial resolution; projection method; error compensation; virtual soft sensor; naphtha; composition model; method of pseudo-components; fractional composition; simulated distillation; boiling point; gas chromatography; solar power; solar systems; photovoltaic panel; mathematical modeling; statistics; correlation; skewness; symmetry; random variable distribution; machine learning; drilling problems; artificial intelligence; risk factor evaluation; gradient boosting; multiple-parameter fractional Fourier transform; image encryption; weighted fractional Fourier transform; information security; autonomous vehicle; path tracking; reinforcement learning; adaptive PID; self-optimizing controller; vehicle control; silicon production; nanoparticles; ore-thermal furnace (OTF); gas cleaning; symmetry; carbon footprint; CFD; ANSYS fluent; droplet impact; superhydrophobic surface; critical velocity; Cassie to Wenzel transition; cross-scale; n/a

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Advanced Digital, Modeling and Control Applies into Various Processes

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July 2024

210 pages

ISBN978-3-7258-1426-8 (Hardback)
ISBN978-3-7258-1425-1 (PDF)

https://doi.org/10.3390/books978-3-7258-1425-1

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This is a Reprint of the Special Issue Advanced Digital, Modeling and Control Applies into Various Processes that was published in

Biology & Life Sciences

Chemistry & Materials Science

Computer Science & Mathematics

Physical Sciences

Summary

This Special Issue reviews advanced digital technologies in modelling and control of technological processes. The methods of numerical modelling, artificial intelligence, machine learning, automatic control, and optimization theory are considered in the published manuscripts of this Special Issue.

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Advanced Digital, Modeling and Control Applies into Various Processes

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