Research graph
References from Continual learning for building energy forecasting via hybrid elastic weight consolidation and synaptic intelligence. Local targets link to admitted publications; unresolved targets remain external evidence.
Achieving net-zero emissions in China's building sector: critiques and strategies of minimizing embodied carbon
10.1016/j.enbuild.2025.115878 · 2025 · External reference
Wind-driven rain effects on annual energy use of low-rise residential buildings in the hot-summer and cold-winter region: a numerical simulation
10.1016/j.energy.2026.141767 · 2026 · External reference
Research on the construction and application of evaluation index system for low-carbon and zero-carbon buildings
10.1016/j.enbuild.2026.117367 · 2026 · External reference
Causal inference of building energy use based on large-scale operational data: evidence from heating and cooling energy use in South Korea
10.1016/j.enbuild.2026.117408 · 2026 · External reference
Performance of energy consumption prediction techniques in classrooms of an educational building in a warm tropical climate
10.1016/j.enbuild.2025.115967 · 2025 · External reference
Thermal storage integration in buildings towards long-term rising EV charging demand: risk-aware and life-cycle optimal design framework
10.1016/j.energy.2026.141164 · 2026 · External reference
Integrating life cycle assessment with GIS and AI for the building sector: a comprehensive review
10.1016/j.enbuild.2026.117095 · 2026 · External reference
DemAEndGAN: cross-modal hourly building energy demand prediction with autoencoders and generative adversarial networks
10.1016/j.enbuild.2026.117334 · 2026 · External reference
Analyzing energy consumption patterns of an educational building through data mining
2021 · External reference
Hot weather and residential hourly electricity demand in Italy
10.1016/j.energy.2019.04.051 · 2019 · External reference
Towards developing a systematic knowledge trend for building energy consumption prediction
2021 · External reference
Study on deep reinforcement learning techniques for building energy consumption forecasting
10.1016/j.enbuild.2019.109675 · 2020 · External reference
A short-term building cooling load prediction method using deep learning algorithms
10.1016/j.apenergy.2017.03.064 · 2017 · External reference
Reconstituted data-driven air conditioning energy consumption prediction system employing occupant-orientated probability model as input
10.1016/j.energy.2023.129799 · 2024 · External reference
Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption
10.1016/j.enbuild.2008.06.013 · 2008 · External reference
Cooling-load prediction by the combination of rough set theory and an artificial neural-network based on data fusion techniques
10.1016/j.apenergy.2005.08.006 · 2006 · External reference
A review of machine learning models and algorithms for short-term forecasting of multi-energy consumption in buildings
2026 · External reference
On hourly forecasting heating energy consumption of HVAC with recurrent neural networks
10.3390/en15145084 · 2022 · External reference
Application of deep learning model in building energy consumption prediction
2022 · External reference
Building thermal load prediction through shallow machine learning and deep learning
10.1016/j.apenergy.2020.114683 · 2020 · External reference
Energy demand forecasting using convolutional neural network and modified war strategy optimization algorithm
2024 · External reference
Data-driven approach to forecast heat consumption of buildings with high-priority weather data
10.3390/buildings12030289 · 2022 · External reference
Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings
10.1038/s41598-022-19935-6 · 2022 · External reference
Forecasting residential energy consumption: single household perspective
2018 · External reference
Energy consumption prediction in residential buildings—an accurate and interpretable machine learning approach combining fuzzy systems with evolutionary optimization
10.3390/en17133242 · 2024 · External reference
A novel improved model for building energy consumption prediction based on model integration
10.1016/j.apenergy.2020.114561 · 2020 · External reference
Machine learning algorithms for predicting energy consumption in educational buildings
10.1155/2024/6812425 · 2024 · External reference
Predicting energy consumption in residential buildings using advanced machine learning algorithms
10.3390/en16093748 · 2023 · External reference
Towards sustainable buildings: predictive modeling of energy consumption with machine learning
10.1016/j.procs.2024.05.004 · 2024 · External reference
Evaluating heating energy consumption in residential buildings using hybrid machine learning models: the case of Parsabad city
10.1016/j.nexres.2025.100721 · 2025 · External reference
BiGTA-net: a hybrid deep learning-based electrical energy forecasting model for building energy management systems
10.3390/systems11090456 · 2023 · External reference
Deep learning in energy modeling: application in smart buildings with distributed energy generation
10.1109/access.2021.3110960 · 2021 · External reference
Deep autoencoder-based hybrid network for building energy consumption forecasting
10.32604/csse.2023.039407 · 2024 · External reference
Effective cross-building transfer learning for HVAC control using deep reinforcement learning and joint action dynamics
10.1016/j.compeleceng.2026.111217 · 2026 · External reference
AI-driven energy forecasting in smart buildings: a federated deep learning framework for edge-fog systems
10.1016/j.future.2026.108490 · 2026 · External reference
Machine learning application in building energy consumption prediction: a comprehensive review
2026 · External reference
Smart energy strategies: leveraging LSTM and LLMs for advanced energy management
10.1016/j.egyai.2025.100642 · 2025 · External reference
A novel building energy consumption prediction method based on multivariate time series alignment and dual-branch joint learning
10.1016/j.energy.2026.141384 · 2026 · External reference
Implementing deep reinforcement learning algorithms for optimal building VRF performance
10.1016/j.applthermaleng.2025.129354 · 2026 · External reference
Short-term load forecasting in smart meters with sliding window-based ARIMA algorithms
10.1007/s40595-018-0119-7 · 2018 · External reference
Deep learning for load forecasting with smart meter data: online adaptive recurrent neural network
10.1016/j.apenergy.2020.116177 · 2021 · External reference
Energy consumption prediction using modified deep CNN-BiLSTM with attention mechanism
10.1016/j.heliyon.2024.e41507 · 2025 · External reference
Building electrical consumption patterns forecasting based on a novel hybrid deep learning model
10.1016/j.rineng.2025.104522 · 2025 · External reference
Deep transfer learning strategy based on TimesBlock-CDAN for predicting thermal environment and air conditioner energy consumption
10.1016/j.apenergy.2024.125188 · 2025 · External reference
Hybrid transformer model with liquid neural networks and learnable encodings for buildings' energy forecasting
10.1016/j.egyai.2025.100489 · 2025 · External reference
Seyis S. Synthetic data generation and energy consumption prediction in district building energy modeling
10.1016/j.enbuild.2025.116716 · 2026 · External reference
Interpretable probabilistic forecasting of building multi-energy loads using residual learning and global attention-enabled transformer
10.1016/j.enbuild.2026.117424 · 2026 · External reference
Transfer learning on transformers for building energy consumption forecasting—a comparative study
10.1016/j.enbuild.2025.115632 · 2025 · External reference
Multi objectives reinforcement learning for smart buildings: a systematic review of algorithms, applications and future perspectives
10.1016/j.enbuild.2025.116045 · 2025 · External reference
Incremental online learning with model augmentation for AI-enabled optimization of building cooling systems
10.1016/j.energy.2026.141622 · 2026 · External reference
Integration of intelligent building operation data based on multi-feature fusion federated learning algorithm
2026 · External reference
Tracing the sources of online prediction errors in building energy consumption: a bias-variance and time-frequency domain based approach
10.1016/j.energy.2026.140566 · 2026 · External reference
Continual learning: a systematic literature review
10.1016/j.neunet.2025.108226 · 2026 · External reference
Adapting to change: a comparison of continual and transfer learning for modeling building thermal dynamics under concept drifts
10.1016/j.enbuild.2025.116868 · 2026 · External reference
Large-scale comparison and demonstration of continual learning for adaptive data-driven building energy prediction
10.1016/j.apenergy.2023.121481 · 2023 · External reference
Variational continual learning
2018 · External reference
Progress & compress: a scalable framework for continual learning
2018 · External reference
Delving into spatiotemporal predictive learning with convolutional RNNs
2017 · External reference
Neural machine translation by jointly learning to align and translate
2015 · External reference
Practical recommendations for gradient-based training of deep architectures
2012 · External reference
Random search for hyper-parameter optimization
2012 · External reference
Adam: a method for stochastic optimization
2015 · External reference
Strictly proper scoring rules, prediction, and estimation
10.1198/016214506000001437 · 2007 · External reference
Overcoming catastrophic forgetting in neural networks
10.1073/pnas.1611835114 · 2017 · External reference
Continual learning through synaptic intelligence
2017 · External reference
Another look at measures of forecast accuracy
10.1016/j.ijforecast.2006.03.001 · 2006 · External reference
The building data genome project 2 database for building energy meter screening
10.1038/s41597-020-00712-x · 2020 · External reference
A complete ensemble empirical mode decomposition with adaptive noise
2011 · External reference
Improved complete ensemble EMD: a suitable tool for biomedical signal processing
10.1016/j.bspc.2014.06.009 · 2014 · External reference
A comprehensive overview on the data driven and large scale based approaches for forecasting of building energy demand: a review
10.1016/j.enbuild.2018.01.017 · 2018 · External reference
Thermal performance prediction of energy-efficient roofs via a CNN-LSTM hybrid model optimized by the sparrow search algorithm
10.1016/j.energy.2026.140683 · 2026 · External reference
Investigation on the CNN-LSTM-MHA-based model for the heating energy consumption prediction of residential buildings considering active and passive factors
10.1016/j.energy.2025.137508 · 2025 · External reference
Continual learning for energy management systems: a review of methods and applications, and a case study
10.1016/j.apenergy.2025.125458 · 2025 · External reference
