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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.
- Format:
- Book
- 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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