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020 _a9783658110390
_z978-3-658-11039-0
024 7 _a10.1007/978-3-658-11039-0
_2doi
040 _aTR-AnTOB
_beng
_cTR-AnTOB
_erda
050 4 _aQA76.9.D35
072 7 _aUMB
_2bicssc
072 7 _aCOM031000
_2bisacsh
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_2thema
072 7 _aURY
_2thema005.74
_223
100 1 _aDannecker, Lars.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aEnergy Time Series Forecasting :
_bEfficient and Accurate Forecasting of Evolving Time Series from the Energy Domain /
_cby Lars Dannecker.
250 _a1st ed. 2015.
264 1 _aWiesbaden :
_bSpringer Fachmedien Wiesbaden :
_bImprint: Springer Vieweg,
_c2015.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aThe 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.
520 _aLars 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. Contents 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-AwareStorage Target Groups Lecturers and Students of Computer Science, especially in the Field of Database Technology, Data Analytics, Time Series Analysis, and Data Mining Data Analysts, Energy Time Series Modeling, Transmission System Operators, Software Developers The Author 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.
650 0 _aData structures (Computer scienc.
650 0 _aInformation theory.
650 0 _aInformation systems.
650 1 4 _aData Structures and Information Theory.
_0http://scigraph.springernature.com/things/product-market-codes/I15009
650 2 4 _aTheory of Computation.
_0http://scigraph.springernature.com/things/product-market-codes/I16005
650 2 4 _aInformation Systems and Communication Service.
_0http://scigraph.springernature.com/things/product-market-codes/I18008
710 2 _aSpringerLink (Online service)
856 4 0 _3Springer eBooks
_zOnline access link to the resource
_uhttps://doi.org/10.1007/978-3-658-11039-0
942 _2lcc
_cEBK
041 _aeng