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020			_a9783319716435 _9978-3-319-71643-5
024	7		_a10.1007/978-3-319-71643-5 _2doi
050		4	_aQ334-342
050		4	_aTA347.A78
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245	1	0	_aData Analytics for Renewable Energy Integration: Informing the Generation and Distribution of Renewable Energy _h[electronic resource] : _b5th ECML PKDD Workshop, DARE 2017, Skopje, Macedonia, September 22, 2017, Revised Selected Papers / _cedited by Wei Lee Woon, Zeyar Aung, Oliver Kramer, Stuart Madnick.
250			_a1st ed. 2017.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2017.
300			_aX, 133 p. 49 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v10691
505	0		_aImitative learning for online planning in microgrids -- A novel central voltage-control strategy for smart LV distribution networks -- Quantifying energy demand in mountainous areas -- Performance analysis of data mining techniques for improving the accuracy of wind power forecast combination -- Evaluation of forecasting methods for very small-scale networks -- Classification cascades of overlapping feature ensembles for energy time series data -- Correlation analysis for determining the potential of home energy management systems in Germany -- Predicting hourly energy consumption. Can regression modeling improve on an autoregressive baseline -- An OPTICS clustering-based anomalous data filtering algorithm for condition monitoring of power equipment -- Argument visualization and narrative approaches for collaborative spatial decision making and knowledge construction: A case study for an offshore wind farm project.
520			_aThis book constitutes revised selected papers from the 5th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2017, held in Skopje, Macedonia, in September 2017. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book and handle topics such as time series forecasting, the detection of faults, cyber security, smart grid and smart cities, technology integration, demand response and many others.
650		0	_aArtificial intelligence.
650		0	_aComputer networks .
650		0	_aData mining.
650		0	_aRenewable energy sources.
650		0	_aEnergy policy.
650		0	_aEnergy and state.
650	1	4	_aArtificial Intelligence.
650	2	4	_aComputer Communication Networks.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aRenewable Energy.
650	2	4	_aEnergy Policy, Economics and Management.
700	1		_aWoon, Wei Lee. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aAung, Zeyar. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKramer, Oliver. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aMadnick, Stuart. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783319716428
776	0	8	_iPrinted edition: _z9783319716442
830		0	_aLecture Notes in Artificial Intelligence, _x2945-9141 ; _v10691
856	4	0	_uhttps://doi.org/10.1007/978-3-319-71643-5
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942			_cSPRINGER
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