Learning-Based Soft Sensing and Predictions for Process Industries : Theory, Methodology and Applications
Language: English
Published by Elsevier Science Okt 2026, 2026
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 170.14
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Add to basketItem description from seller
Neuware - Learning-Based Soft Sensing and Predictions for Process Industries: Theory, Methodology and Applications covers prediction and soft sensing in industrial processes that are subject to specific challenges with AI-empowered learning algorithms. With the aid of a data-driven modeling strategy, the book explores the problems of industrial prediction and soft sensing and formulates a series of learning-based theory, methodologies, and applications. The book introduces the basics of prediction and soft sensing backgrounds, including different categories of prediction theory. Secondly, covers the foundations of machine learning methodologies, including supervised learning prediction, semi-supervised, and self-supervised prediction. Finally, the book examines novel learning-based models/architectures.
Seller Inventory # 9780443367595
- Title
- Learning-Based Soft Sensing and Predictions for Process Industries : Theory, Methodology and Applications
- Author
- Hamid Reza Karimi
- Publisher
- Elsevier Science Okt 2026
- Publication year
- 2026
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0443367590
- ISBN 13
- 9780443367595
- Item weight
- 449 grams
- Dimensions
- 228x152x14 mm
- Covers the benefits and an explanation of recent developments in prediction and soft sensing systems
- Unifies existing and emerging concepts surrounding advanced prediction models/architectures
- Provides a series of the latest results in, including, but not limited to, supervised learning, semi-supervised learning, self-supervised learning, probabilistic learning
"Synopsis" may belong to another edition of this title.
About the Author
Dr Yongxiang Lei received the B.Sc. Degree in Automation from the University of South China in 2017 and an M.Sc. in control engineering from Central South University, Changsha, China in 2020. In 2024, received his Ph.D. degree in Mechanical Engineering from Politecnico di Milano. Dr Lei’s research interests are in the areas of machine learning, prediction & control, industrial process modeling, simulation and application, soft sensing.
"About the title" may belong to another edition of this title.
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