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Data Analytics for Renewable Energy Integration [electronic resource] : Third ECML PKDD Workshop, DARE 2015, Porto, Portugal, September 11, 2015. Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 9518Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: VII, 155 p. 94 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319274300
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
Imitative 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.
In: Springer Nature eBookSummary: This book constitutes revised selected papers from the third ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2015, held in Porto, Portugal, in September 2015. The 10 papers presented in this volume were carefully reviewed and selected for inclusion in this book.
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Imitative 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.

This book constitutes revised selected papers from the third ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2015, held in Porto, Portugal, in September 2015. The 10 papers presented in this volume were carefully reviewed and selected for inclusion in this book.

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