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024 7 _a10.1007/978-3-319-71643-5
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050 4 _aQ334-342
050 4 _aTA347.A78
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072 7 _aCOM004000
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082 0 4 _a006.3
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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
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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.
_93407
650 0 _aComputer networks .
_931572
650 0 _aData mining.
_93907
650 0 _aRenewable energy sources.
_94906
650 0 _aEnergy policy.
_914226
650 0 _aEnergy and state.
_931819
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputer Communication Networks.
_9106732
650 2 4 _aData Mining and Knowledge Discovery.
_9106733
650 2 4 _aRenewable Energy.
_913722
650 2 4 _aEnergy Policy, Economics and Management.
_931820
700 1 _aWoon, Wei Lee.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9106734
700 1 _aAung, Zeyar.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9106735
700 1 _aKramer, Oliver.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9106736
700 1 _aMadnick, Stuart.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9106737
710 2 _aSpringerLink (Online service)
_9106738
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
_9106739
856 4 0 _uhttps://doi.org/10.1007/978-3-319-71643-5
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