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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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull?autore
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.
Dalla quarta di copertina
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.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer-Nature New York Inc
- Data di pubblicazione2018
- ISBN 10 3319940503
- ISBN 13 9783319940502
- RilegaturaCopertina rigida
- LinguaInglese
- Numero edizione1
- Numero di pagine460
- Contatto del produttorenon disponibile
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Data-Driven Prediction for Industrial Processes and Their Applications
Editore:
Springer International Publishing, 2018
ISBN 10: 3319940503
ISBN 13: 9783319940502
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Features data-driven modeling algorithms for different industrial prediction requirementsDiscusses multi-scale (short, median, long) prediction, multi-type prediction (time series and factor-based), and interval-based prediction. Codice articolo 226328079
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Data-Driven Prediction for Industrial Processes and Their Applications
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Springer International Publishing Aug 2018, 2018
ISBN 10: 3319940503
ISBN 13: 9783319940502
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 460 pp. Englisch. Codice articolo 9783319940502
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Data-Driven Prediction for Industrial Processes and Their Applications
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Springer International Publishing, 2018
ISBN 10: 3319940503
ISBN 13: 9783319940502
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783319940502
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Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science)
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Data-Driven Prediction for Industrial Processes and Their Applications (Information Fusion and Data Science)
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DATA-DRIVEN PREDICTION FOR INDUSTRIAL PROCESSES AND THEIR APPLICATIONS-
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