Interpretable machine learning for building energy management: A state-of-the-art review

Advances in Applied Energy, Год журнала: 2023, Номер 9, С. 100123 - 100123

Опубликована: Янв. 13, 2023

Machine learning has been widely adopted for improving building energy efficiency and flexibility in the past decade owing to ever-increasing availability of massive operational data. However, it is challenging end-users understand trust machine models because their black-box nature. To this end, interpretability attracted increasing attention recent studies helps users decisions made by these models. This article reviews previous that interpretable techniques management analyze how model improved. First, are categorized according application stages techniques: ante-hoc post-hoc approaches. Then, analyzed detail specific with critical comparisons. Through review, we find broad faces following significant challenges: (1) different terminologies used describe which could cause confusion, (2) performance ML tasks difficult compare, (3) current prevalent such as SHAP LIME can only provide limited interpretability. Finally, discuss future R&D needs be accelerate management.

Язык: Английский

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Interpretable building energy consumption forecasting using spectral clustering algorithm and temporal fusion transformers architecture

Applied Energy, Год журнала: 2023, Номер 349, С. 121607 - 121607

Опубликована: Июль 27, 2023

Язык: Английский

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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects

Energy & Fuels, Год журнала: 2024, Номер 38(3), С. 1692 - 1712

Опубликована: Янв. 19, 2024

Modern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimization and model prediction. The effective utilization ML the development scaling up systems needs a high degree accountability. However, most approaches currently use termed black box since their work is difficult to comprehend. Explainable artificial intelligence (XAI) an attractive option solve issue poor interoperability black-box methods. This review investigates relationship between (RE) XAI. It emphasizes potential advantages XAI improving performance efficacy RE systems. realized that although integration with has enormous alter how produced consumed, possible hazards barriers remain be overcome, particularly concerning transparency, accountability, fairness. Thus, extensive research required address societal ethical implications using create standardized data sets evaluation metrics. In summary, this paper shows potential, perspectives, opportunities, challenges application system management operation aiming target efficient energy-use goals more sustainable trustworthy future.

Язык: Английский

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Interpretation of convolutional neural network-based building HVAC fault diagnosis model using improved layer-wise relevance propagation

Energy and Buildings, Год журнала: 2023, Номер 286, С. 112949 - 112949

Опубликована: Март 2, 2023

Язык: Английский

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A compound approach for ten-day runoff prediction by coupling wavelet denoising, attention mechanism, and LSTM based on GPU parallel acceleration technology

Earth Science Informatics, Год журнала: 2024, Номер 17(2), С. 1281 - 1299

Опубликована: Янв. 10, 2024

Язык: Английский

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Short-term cooling and heating loads forecasting of building district energy system based on data-driven models

Energy and Buildings, Год журнала: 2023, Номер 298, С. 113513 - 113513

Опубликована: Сен. 4, 2023

Язык: Английский

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A Review of Data-Driven Building Energy Prediction

Buildings, Год журнала: 2023, Номер 13(2), С. 532 - 532

Опубликована: Фев. 15, 2023

Building energy consumption prediction has a significant effect on control, design optimization, retrofit evaluation, price guidance, and prevention control of COVID-19 in buildings, providing guarantee for efficiency carbon neutrality. This study reviews 116 research papers data-driven building from the perspective data machine learning algorithms discusses feasible techniques across time scales, levels, types context factors affecting prediction. The review results revealed that outdoor dry-bulb temperature is vital factor consumption. In prediction, preprocessing enables feature extraction types, hyperparameter optimization scales layers.

Язык: Английский

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A hybrid forecasting method for cooling load in large public buildings based on improved long short term memory

Journal of Building Engineering, Год журнала: 2023, Номер 76, С. 107238 - 107238

Опубликована: Июль 3, 2023

Язык: Английский

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An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting

The Science of The Total Environment, Год журнала: 2024, Номер 929, С. 172465 - 172465

Опубликована: Апрель 12, 2024

Язык: Английский

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Fault diagnosis for cross-building energy systems based on transfer learning and model interpretation

Journal of Building Engineering, Год журнала: 2024, Номер 91, С. 109424 - 109424

Опубликована: Апрель 22, 2024

Язык: Английский

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