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Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032472065 ISBN 13: 9781032472065
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:an exclusive section on essential preprocessing approaches for the data-driven modela detailed overview of data-driven model applications to power system planning and operational activitiesspecific focus on developing forecasting models for renewable generations such as solar PV and wind power, andshowcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworksThis book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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ISBN 10: 1032472065 ISBN 13: 9781032472065
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:an exclusive section on essential preprocessing approaches for the data-driven modela detailed overview of data-driven model applications to power system planning and operational activitiesspecific focus on developing forecasting models for renewable generations such as solar PV and wind power, andshowcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworksThis book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: Taylor & Francis Ltd, London, 2024
ISBN 10: 1032472065 ISBN 13: 9781032472065
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:an exclusive section on essential preprocessing approaches for the data-driven modela detailed overview of data-driven model applications to power system planning and operational activitiesspecific focus on developing forecasting models for renewable generations such as solar PV and wind power, andshowcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworksThis book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel. This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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In den WarenkorbBuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:an exclusive section on essential preprocessing approaches for the data-driven modela detailed overview of data-driven model applications to power system planning and operational activitiesspecific focus on developing forecasting models for renewable generations such as solar PV and wind power, andshowcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworksThis book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel. 238 pp. 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. B Rajanarayan Prusty (Senior Member, IEEE) is a Professor and Associate Dean Research in the School of Engineering, Galgotias University, Greater Noida, India. He obtained his Ph.D. from the National Institute of Technology Karnataka, Su.
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In den WarenkorbBuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:an exclusive section on essential preprocessing approaches for the data-driven modela detailed overview of data-driven model applications to power system planning and operational activitiesspecific focus on developing forecasting models for renewable generations such as solar PV and wind power, andshowcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworksThis book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.
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