Information Fusion and Data Science
cover

Data-Driven Prediction for Industrial Processes and Their Applications

Authors: Zhao, Jun, Wang, Wei, Sheng, Chunyang

  • Features data-driven modeling algorithms for different industrial prediction requirements
  • Discusses multi-scale (short, median, long) prediction, multi-type prediction (time series and factor-based), and interval-based prediction
  • Includes case studies based on real-world industrial predictions
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eBook 107,09 €
price for Spain (gross)
  • ISBN 978-3-319-94051-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 135,19 €
price for Spain (gross)
  • ISBN 978-3-319-94050-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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.

About the authors

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.

Table of contents (9 chapters)

  • Introduction

    Zhao, Jun (et al.)

    Pages 1-11

  • Data Preprocessing Techniques

    Zhao, Jun (et al.)

    Pages 13-52

  • Industrial Time Series Prediction

    Zhao, Jun (et al.)

    Pages 53-119

  • Factor-Based Industrial Process Prediction

    Zhao, Jun (et al.)

    Pages 121-157

  • Industrial Prediction Intervals with Data Uncertainty

    Zhao, Jun (et al.)

    Pages 159-222

Buy this book

eBook 107,09 €
price for Spain (gross)
  • ISBN 978-3-319-94051-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 135,19 €
price for Spain (gross)
  • ISBN 978-3-319-94050-2
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Data-Driven Prediction for Industrial Processes and Their Applications
Authors
Series Title
Information Fusion and Data Science
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG, part of Springer Nature
eBook ISBN
978-3-319-94051-9
DOI
10.1007/978-3-319-94051-9
Hardcover ISBN
978-3-319-94050-2
Series ISSN
2510-1528
Edition Number
1
Number of Pages
XVI, 443
Number of Illustrations
39 b/w illustrations, 128 illustrations in colour
Topics