Energy Time Series Forecasting : Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain - neues Buch
2015, ISBN: 9783658110390
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing… Mehr…
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2015, ISBN: 9783658110390
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing… Mehr…
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ISBN: 3658110392
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2015, ISBN: 9783658110390
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2015, ISBN: 9783658110390
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Energy Time Series Forecasting : Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain - neues Buch
2015, ISBN: 9783658110390
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing… Mehr…
2015, ISBN: 9783658110390
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing… Mehr…
ISBN: 3658110392
Energy Time Series Forecasting ab 74.99 € als pdf eBook: Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain. Aus dem Bereich: eBooks, Sachthemen & Ratgeber,… Mehr…
2015, ISBN: 9783658110390
Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain, eBooks, eBook Download (PDF), 1st ed. 2015, [PU: Springer Fachmedien Wiesbaden GmbH], Seiten: 231, Sprin… Mehr…
2015, ISBN: 9783658110390
Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain, eBooks, eBook Download (PDF), Auflage, [PU: Springer Vieweg], [ED: 1], Springer Vieweg, 2015
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Detailangaben zum Buch - Energy Time Series Forecasting
EAN (ISBN-13): 9783658110390
ISBN (ISBN-10): 3658110392
Erscheinungsjahr: 2015
Herausgeber: Springer Fachmedien Wiesbaden GmbH
Buch in der Datenbank seit 2016-08-28T22:11:53+02:00 (Berlin)
Detailseite zuletzt geändert am 2022-12-20T07:42:42+01:00 (Berlin)
ISBN/EAN: 3658110392
ISBN - alternative Schreibweisen:
3-658-11039-2, 978-3-658-11039-0
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: danne, dannecker, reinhold
Titel des Buches: tim, dannecker, energy forecasting
Daten vom Verlag:
Autor/in: Lars Dannecker
Titel: Energy Time Series Forecasting - Efficient and Accurate Forecasting of Evolving Time Series from the Energy Domain
Verlag: Springer Vieweg; Springer Fachmedien Wiesbaden GmbH
231 Seiten
Erscheinungsjahr: 2015-08-06
Wiesbaden; DE
Sprache: Englisch
53,49 € (DE)
55,00 € (AT)
59,00 CHF (CH)
Available
XIX, 231 p. 92 illus., 19 illus. in color.
EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Algorithmen und Datenstrukturen; Verstehen; Der Europäische Strommarkt; Electric Power Consumption; Elektrizitätsverbrauch; Energiebedarf in der Zukunft; Energiemanagement und -prognose; Energy Data Management and Forecasting; Erneuerbarre Energien; Future Demand in Electricity; Renewable Energy Sources; The European Electricity Market; C; Data Structures and Information Theory; Theory of Computation; Computer Communication Networks; Computer Science; Informationstheorie; Theoretische Informatik; Netzwerk-Hardware; BC
Nominated for the Georg-Helm-Preis 2015 awarded by the Technische Universität Dresden.
The European Electricity Market: A Market Study.- The Current State of Energy Data Management and Forecasting.- The Online Forecasting Process: Efficiently Providing Accurate Predictions.- Optimizations on the Logical Layer: Context-Aware Forecasting.- Optimizations on the Physical Layer: A Forecast-Model-Aware Storage.
Lars Dannecker holds a diploma in media computer science from the Technische Universität Dresden and is pursuing a doctorate as a member of the Database Technology Group led by Prof. Dr.-Ing. Wolfgang Lehner.
Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing the process to adapt to different situations and applications. Improving the forecasting efficiency is a key pre-requisite for ensuring stable electricity grids in the face of an increasing amount of renewable energy sources. It is also important to facilitate the move from static day ahead electricity trading towards more dynamic real-time marketplaces. The online forecasting process is realized by a number of approaches on the logical as well as on the physical layer that we introduce in the course of this book.
Nominated for the Georg-Helm-Preis 2015 awarded by the Technische Universität Dresden.
Lars Dannecker holds a diploma in media computer science from the Technische Universität Dresden and is pursuing a doctorate as a member of the Database Technology Group led by Prof. Dr.-Ing. Wolfgang Lehner.
Contents Target Groups The AuthorStudy in computer science Includes supplementary material: sn.pub/extras
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