Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques

Journal of Building Engineering, Journal Year: 2021, Volume and Issue: 45, P. 103406 - 103406

Published: Oct. 12, 2021

Language: Английский

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Artificial intelligence-based solutions for climate change: a review

Environmental Chemistry Letters, Journal Year: 2023, Volume and Issue: 21(5), P. 2525 - 2557

Published: June 13, 2023

Abstract Climate change is a major threat already causing system damage to urban and natural systems, inducing global economic losses of over $500 billion. These issues may be partly solved by artificial intelligence because integrates internet resources make prompt suggestions based on accurate climate predictions. Here we review recent research applications in mitigating the adverse effects change, with focus energy efficiency, carbon sequestration storage, weather renewable forecasting, grid management, building design, transportation, precision agriculture, industrial processes, reducing deforestation, resilient cities. We found that enhancing efficiency can significantly contribute impact change. Smart manufacturing reduce consumption, waste, emissions 30–50% and, particular, consumption buildings 30–50%. About 70% gas industry utilizes technologies enhance accuracy reliability forecasts. Combining smart grids optimize power thereby electricity bills 10–20%. Intelligent transportation systems dioxide approximately 60%. Moreover, management design cities through application further promote sustainability.

Language: Английский

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Towards intelligent building energy management: AI-based framework for power consumption and generation forecasting

Energy and Buildings, Journal Year: 2022, Volume and Issue: 279, P. 112705 - 112705

Published: Dec. 5, 2022

Language: Английский

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Machine learning for energy performance prediction at the design stage of buildings

Energy Sustainable Development/Energy for sustainable development, Journal Year: 2021, Volume and Issue: 66, P. 12 - 25

Published: Nov. 17, 2021

Language: Английский

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A Hybrid Model with Applying Machine Learning Algorithms and Optimization Model to Forecast Greenhouse Gas Emissions with Energy Market Data

Sustainable Cities and Society, Journal Year: 2022, Volume and Issue: 82, P. 103886 - 103886

Published: April 11, 2022

Language: Английский

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Explainable artificial intelligence for building energy performance certificate labelling classification

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 355, P. 131626 - 131626

Published: April 9, 2022

Language: Английский

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Principles, research status, and prospects of feature engineering for data-driven building energy prediction: A comprehensive review

Journal of Building Engineering, Journal Year: 2022, Volume and Issue: 58, P. 105028 - 105028

Published: Aug. 6, 2022

Language: Английский

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A spatial-temporal layer-wise relevance propagation method for improving interpretability and prediction accuracy of LSTM building energy prediction

Energy and Buildings, Journal Year: 2022, Volume and Issue: 271, P. 112317 - 112317

Published: July 16, 2022

Language: Английский

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Performance evaluation of sequence-to-sequence-Attention model for short-term multi-step ahead building energy predictions

Energy, Journal Year: 2022, Volume and Issue: 259, P. 124915 - 124915

Published: Aug. 10, 2022

Language: Английский

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Modeling energy-efficient building loads using machine-learning algorithms for the design phase

Energy and Buildings, Journal Year: 2023, Volume and Issue: 283, P. 112807 - 112807

Published: Jan. 20, 2023

Language: Английский

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