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Data Analytics for Renewable Energy Integration : Third ECML PKDD Workshop, DARE 2015, Porto, Portugal, September 11, 2015. Revised Selected Papers / edited by Wei Lee Woon, Zeyar Aung, Stuart Madnick.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Woon, Wei Lee, Editor.
Aung, Zeyar, Editor.
Madnick, Stuart., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 9518
Lecture Notes in Artificial Intelligence, 2945-9141 ; 9518
Language:
English
Subjects (All):
Artificial intelligence.
Data mining.
Renewable energy sources.
Computer science-Mathematics.
Energy policy.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Renewable Energy.
Mathematics of Computing.
Energy Policy, Economics and Management.
Local Subjects:
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Renewable Energy.
Mathematics of Computing.
Energy Policy, Economics and Management.
Physical Description:
1 online resource (VII, 155 pages) : 94 illustrations in color.
Edition:
1st ed. 2015.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2015.
System Details:
text file PDF
Summary:
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.
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.
Other Format:
Printed edition:
ISBN:
978-3-319-27430-0
9783319274300
Access Restriction:
Restricted for use by site license.

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