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Data Analytics for Renewable Energy Integration. Technologies, Systems and Society : 6th ECML PKDD Workshop, DARE 2018, Dublin, Ireland, September 10, 2018, Revised Selected Papers / edited by Wei Lee Woon, Zeyar Aung, Alejandro Catalina Feliú, Stuart Madnick.

SpringerLink Books Computer Science (2011-2024) Available online

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Format:
Book
Contributor:
Woon, Wei Lee, Editor.
Aung, Zeyar, Editor.
Catalina Feliú, Alejandro., Editor.
Madnick, Stuart., Editor.
SpringerLink (Online service)
Series:
Computer Science (SpringerNature-11645)
Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 11325
Lecture Notes in Artificial Intelligence, 2945-9141 ; 11325
Language:
English
Subjects (All):
Artificial intelligence.
Computer networks.
Data mining.
Renewable energy sources.
Energy policy.
Artificial Intelligence.
Computer Communication Networks.
Data Mining and Knowledge Discovery.
Renewable Energy.
Energy Policy, Economics and Management.
Local Subjects:
Artificial Intelligence.
Computer Communication Networks.
Data Mining and Knowledge Discovery.
Renewable Energy.
Energy Policy, Economics and Management.
Physical Description:
1 online resource (X, 167 pages) : 75 illustrations, 65 illustrations in color.
Edition:
1st ed. 2018.
Contained In:
Springer Nature eBook
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2018.
System Details:
text file PDF
Summary:
This book constitutes the revised selected papers from the 6th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2018, held in Dublin, Ireland, in September 2018. The 9 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.
Contents:
Mathematical Optimization of Design Parameters of Photovoltaic Module
Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features
Sampling Strategies for Representative Time Series in Load Flow Calculations
Probabilistic Graphs for Sensor Data-driven Modelling of Power Systems at Scale
Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation
Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access
Contribution Machine learning as Surrogate to Building Performance Simulation: A Building Design Optimization Application
Clustering River Basins using Time-Series Data Mining on Hydroelectric Energy Generation
Short-Term Electricity Consumption Forecast using Datasets of Various Granularities?
Intelligent Monitoring of Transformer Insulation using Convolutional Neural Networks
Nonintrusive Load Monitoring based on Deep Learning
Urban Climate Data Sensing, Warehousing, and Analysis: A Case Study in the City of Abu Dhabi, United Arab Emirates.
Other Format:
Printed edition:
ISBN:
978-3-030-04303-2
9783030043032
Access Restriction:
Restricted for use by site license.

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