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Data Analytics for Renewable Energy Integration. Technologies, Systems and Society

Overview of attention for book
Cover of 'Data Analytics for Renewable Energy Integration. Technologies, Systems and Society'

Table of Contents

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    Book Overview
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    Chapter 1 Mathematical Optimization of Design Parameters of Photovoltaic Module
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    Chapter 2 Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features
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    Chapter 3 Sampling Strategies for Representative Time Series in Load Flow Calculations
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    Chapter 4 Probabilistic Graphs for Sensor Data-Driven Modelling of Power Systems at Scale
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    Chapter 5 Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation
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    Chapter 6 Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access
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    Chapter 7 Machine Learning as Surrogate to Building Performance Simulation: A Building Design Optimization Application
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    Chapter 8 Clustering River Basins Using Time-Series Data Mining on Hydroelectric Energy Generation
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    Chapter 9 Short-Term Electricity Consumption Forecast Using Datasets of Various Granularities
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    Chapter 10 Intelligent Monitoring of Transformer Insulation Using Convolutional Neural Networks
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    Chapter 11 Nonintrusive Load Monitoring Based on Deep Learning
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    Chapter 12 Urban Climate Data Sensing, Warehousing, and Analysis: A Case Study in the City of Abu Dhabi, United Arab Emirates
Attention for Chapter 9: Short-Term Electricity Consumption Forecast Using Datasets of Various Granularities
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Citations

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Chapter title
Short-Term Electricity Consumption Forecast Using Datasets of Various Granularities
Chapter number 9
Book title
Data Analytics for Renewable Energy Integration. Technologies, Systems and Society
Published by
Springer, Cham, September 2018
DOI 10.1007/978-3-030-04303-2_9
Book ISBNs
978-3-03-004302-5, 978-3-03-004303-2
Authors

Yusuf Arslan, Aybike Şimşek Dilbaz, Seyda Ertekin, Pinar Karagoz, Aysenur Birturk, Sinan Eren, Dilek Küçük

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 20%
Lecturer 1 20%
Student > Master 1 20%
Unknown 2 40%
Readers by discipline Count As %
Engineering 2 40%
Unknown 3 60%

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