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Data-Driven Prediction for Industrial Processes and Their Applications

Information Fusion and Data Science

Format: Hardback
Publisher: Springer International Publishing AG, Cham, Switzerland
Published: 30th Aug 2018
Dimensions: w 156mm h 234mm d 25mm
Weight: 819g
ISBN-10: 3319940503
ISBN-13: 9783319940502
Barcode No: 9783319940502
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Synopsis
This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.

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