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Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
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Hardcover. Zustand: new. Hardcover. The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. The book explores the field of model predictive control (MPC). While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Zustand: New.
Sprache: Englisch
Verlag: Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences.
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In den WarenkorbZustand: new. Questo è un articolo print on demand.
Sprache: Englisch
Verlag: Springer, Berlin, Springer Nature Switzerland, Springer, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. 224 pp. Englisch.
Sprache: Englisch
Verlag: Springer Nature Switzerland, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
Anbieter: preigu, Osnabrück, Deutschland
Buch. Zustand: Neu. Model Predictive Control | Engineering Methods for Economists | Aris Daniilidis (u. a.) | Buch | xii | Englisch | 2025 | Springer Nature Switzerland | EAN 9783031852558 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
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In den WarenkorbHardcover. Zustand: new. Hardcover. The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. The book explores the field of model predictive control (MPC). While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbZustand: New. Print on Demand.
Sprache: Englisch
Verlag: Springer Nature Switzerland, Springer Nature Switzerland Jun 2025, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 236 pp. Englisch.
Sprache: Englisch
Verlag: Springer International Publishing AG, Cham, 2025
ISBN 10: 3031852559 ISBN 13: 9783031852558
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Hardcover. Zustand: new. Hardcover. The book explores the field of model predictive control (MPC). It reports on the latest developments in MPC, current applications, and presents various subfields of MPC. The book features topics such as uncertain and stochastic MPC variants, learning and neural network approaches, easy-to-use numerical implementations as well as multi-agent systems and scheduling and coordination tasks. While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. The book explores the field of model predictive control (MPC). While MPC is rooted in engineering science, this book illustrates the potential of using MPC theory and methods in non-engineering sciences and applications such as economics, finance, and environmental sciences. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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