Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science) - Hardcover

Book 2 of 9: Information Fusion and Data Science

Zhao, Jun; Wang, Wei; Sheng, Chunyang

 
9783319940502: Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science)
Hardcover
ISBN 10: 3319940503 ISBN 13: 9783319940502
Publisher: Springer, 2018

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 withinthe machine learning and data analysis and mining communities.

"synopsis" may belong to another edition of this title.

About the Author

Jun Zhao is currently a Professor with the School of Control Science and Engineering, Dalian University of Technology, China.

Chunyang Sheng is currently a lecturer with the School of Electrical Engineering and Automation, Shandong University of Science and Technology, China. 

Wei Wang is currently a Professor with the School of Control Science and Engineering, Dalian University of Technology, China.

From the Back Cover

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 withinthe machine learning and data analysis and mining communities.

"About this title" may belong to another edition of this title.

Publisher
Springer
Publication date
2018
Language
English
ISBN 10 
3319940503
ISBN 13 
9783319940502
Binding
Hardcover
Edition number
1
Number of pages
459

Other Popular Editions of the Same Title

9783030067854: Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science)

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ISBN 10:  3030067858 ISBN 13:  9783030067854
Publisher: Springer, 2018
Softcover