Verlag: Springer International Publishing, Springer International Publishing, 2018
ISBN 10: 3030067858 ISBN 13: 9783030067854
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Springer International Publishing, 2018
ISBN 10: 3319940503 ISBN 13: 9783319940502
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbBuch. Zustand: 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.
Verlag: Springer International Publishing, Springer International Publishing Dez 2018, 2018
ISBN 10: 3030067858 ISBN 13: 9783030067854
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 139,09
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In den WarenkorbTaschenbuch. Zustand: Neu. 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 withinthe machine learning and data analysis and mining communities.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 460 pp. Englisch.
Verlag: Springer International Publishing, Springer International Publishing Aug 2018, 2018
ISBN 10: 3319940503 ISBN 13: 9783319940502
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 139,09
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In den WarenkorbBuch. Zustand: Neu. 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 withinthe machine learning and data analysis and mining communities.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 460 pp. Englisch.
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Verlag: Springer International Publishing, 2018
ISBN 10: 3030067858 ISBN 13: 9783030067854
Sprache: Englisch
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In den WarenkorbZustand: 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.
Verlag: Springer International Publishing, 2018
ISBN 10: 3319940503 ISBN 13: 9783319940502
Sprache: Englisch
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In den WarenkorbGebunden. Zustand: 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.
Verlag: Springer International Publishing Dez 2018, 2018
ISBN 10: 3030067858 ISBN 13: 9783030067854
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: 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.
Verlag: Springer International Publishing Aug 2018, 2018
ISBN 10: 3319940503 ISBN 13: 9783319940502
Sprache: Englisch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
EUR 139,09
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In den WarenkorbBuch. Zustand: 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.
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