Learning-Based Predictions and Soft Sensing for Process Industries
Theory, Methodology and Applications
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Erscheint vorauss. 1. Juli 2026
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Learning-Based Predictions and Soft Sensing for Process Industries covers prediction and soft sensing in industrial processes 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, methodology and applications. The book introduces the basics of the prediction and soft sensing backgrounds, including the different categories of prediction theory. Secondly, the book looks at the foundations of machine learning m...
Learning-Based Predictions and Soft Sensing for Process Industries covers prediction and soft sensing in industrial processes 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, methodology and applications. The book introduces the basics of the prediction and soft sensing backgrounds, including the different categories of prediction theory. Secondly, the book looks at the foundations of machine learning methodologies, which covers supervised learning prediction, semi-supervised and self-supervised prediction. Finally, the book examines some novel learning-based models/architectures
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