Novel domestic building energy consumption dataset: 1D timeseries and 2D Gramian Angular Fields representation-Reference-Cited by-同舟云学术

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Novel domestic building energy consumption dataset: 1D timeseries and 2D Gramian Angular Fields representation

Published:2023-04 Issue: Volume:47 Page:108985
ISSN:2352-3409
Container-title:Data in Brief
language:en
Short-container-title:Data in Brief

Author:

Alsalemi Abdullah^ORCID,Amira Abbes^ORCID,Malekmohamadi Hossein^ORCID,Diao Kegong

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference8 articles.

1. Buildings energy efficiency analysis and classification using various machine learning technique classifiers;Benavente-Peces;Energies,2020

2. Data on residential nearly Zero Energy Buildings (nZEB) design in Eastern Europe;Attia;Data Brief,2022

3. Behavioral economics and energy conservation – a systematic review of non-price interventions and their causal effects;Andor;Ecol. Econ.,2018

4. Facilitating deep learning for edge computing: a case study on data classification;Alsalemi,2022

5. Day-ahead solar irradiation forecasting utilizing gramian angular field and convolutional long short-term memory;Hong;IEEE Access,2020

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3. Twining Buildings: A Methodological Framework for Design and Implementation using Home Assistant Technology;2023 International Conference on Electrical, Communication and Computer Engineering (ICECCE);2023-12-30

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