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Deep belief network based deterministic and probabilistic wind speed forecasting approach

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Deep Neural Network Based Demand Side Short Term Load Forecasting

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A comprehensive review on deep learning approaches for short-term load forecasting

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Tackling climate change with machine learning

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A hybrid deep transfer learning strategy for short term cross-building energy prediction

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Data driven parallel prediction of building energy consumption using generative adversarial nets

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Dual stream network with attention mechanism for photovoltaic power forecasting

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A multi-energy load prediction model based on deep multi-task learning and ensemble approach for regional integrated energy systems

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Cooling load prediction and optimal operation of HVAC systems using a multiple nonlinear regression model

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A Review on Machine Learning Strategies for Real-World Engineering Applications

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Improved Deep Belief Network for Short-Term Load Forecasting Considering Demand-Side Management

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Advances of machine learning in multi-energy district communities‒ mechanisms, applications and perspectives

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A Review of Deep Learning Techniques for Forecasting Energy Use in Buildings

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Solar irradiance forecasting based on direct explainable neural network

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Multi-energy net load forecasting for integrated local energy systems with heterogeneous prosumers

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Energy Consumption Prediction Using Machine Learning; A ReviewPreprint

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Machine Learning for Harnessing Thermal Energy: From Materials Discovery to System Optimization

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Improving cooling load prediction reliability for HVAC system using Monte-Carlo simulation to deal with uncertainties in input variables

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Echo state network based ensemble approach for wind power forecasting

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Strategic potential of multi-energy system towards carbon neutrality: A forward-looking overview

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A generic prediction interval estimation method for quantifying the uncertainties in ultra-short-term building cooling load prediction

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A Hybrid Forecasting Method for Solar Output Power Based on Variational Mode Decomposition, Deep Belief Networks and Auto-Regressive Moving Average

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Machine Learning Based Hybrid System for Imputation and Efficient Energy Demand Forecasting

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Wind Speed Forecasting Based on Extreme Gradient Boosting

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Advances in Deep Learning Techniques for Short-term Energy Load Forecasting Applications: A Review

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Accurate forecasting of building energy consumption via a novel ensembled deep learning method considering the cyclic feature

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Forecasting performance comparison of two hybrid machine learning models for cooling load of a large-scale commercial building

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PSO-Stacking improved ensemble model for campus building energy consumption forecasting based on priority feature selection

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A new energy consumption prediction method for chillers based on GraphSAGE by combining empirical knowledge and operating data

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ESAENARX and DE-RELM: Novel schemes for big data predictive analytics of electricity load and price

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Analysis of hourly cooling load prediction accuracy with data-mining approaches on different training time scales

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Developing a multi-level intrusion detection system using hybrid-DBN

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A CNN‐BiLSTM based deep learning model for mid‐term solar radiation prediction

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A Review of Energy Consumption Forecasting in Smart Buildings: Methods, Input Variables, Forecasting Horizon and Metrics

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A novel ensemble method for hourly residential electricity consumption forecasting by imaging time series

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Elastic weight consolidation-based adaptive neural networks for dynamic building energy load prediction modeling

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Modal decomposition based ensemble learning for ground source heat pump systems load forecasting

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District Heating Load Prediction Algorithm Based on Feature Fusion LSTM Model

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Performance evaluation of short-term cross-building energy predictions using deep transfer learning strategies

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Probabilistic load forecasting for integrated energy systems using attentive quantile regression temporal convolutional network

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Multi-task learning based multi-energy load prediction in integrated energy system

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An Improved Hybrid Model for Short Term Power Load Prediction

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Short-term PV power forecasting based on time series expansion and high-order fuzzy cognitive maps

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An improved transfer learning strategy for short-term cross-building energy prediction using data incremental

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Meta-learning strategy based on user preferences and a machine recommendation system for real-time cooling load and COP forecasting

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Energy consumption prediction in cement calcination process: A method of deep belief network with sliding window

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Research on the combined forecasting model of cooling load based on IVMD-WOA-LSSVM

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Short-term forecast model of cooling load using load component disaggregation

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Modeling of H2S solubility in ionic liquids using deep learning: A chemical structure-based approach

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A Review on Deep Learning with Focus on Deep Recurrent Neural Network for Electricity Forecasting in Residential Building

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Algorithmic conservation in a changing climate

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Application of artificial neural networks in predicting the performance of ice thermal energy storage systems

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Short term load forecasting with markovian switching distributed deep belief networks

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Machine Learning Applications for Smart Building Energy Utilization: A Survey

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A novel robust ensemble model integrated extreme learning machine with multi-activation functions for energy modeling and analysis: Application to petrochemical industry

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Review of load data analytics using deep learning in smart grids: Open load datasets, methodologies, and application challenges

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Performance assessment of cross office building energy prediction in the same region using the domain adversarial transfer learning strategy

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Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning

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A novel hybrid model based on evolving multi-quantile long and short-term memory neural network for ultra-short-term probabilistic forecasting of photovoltaic power

Zhu, J., & He, Y. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.124601 · Cited by 29

Air-Conditioning Load Forecasting for Prosumer Based on Meta Ensemble Learning

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Statistical and machine learning approaches for energy efficient buildings

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Real-time automatic control of multi-energy system for smart district community: A coupling ensemble prediction model and safe deep reinforcement learning

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Light-stacking strengthened fusion based building energy consumption prediction framework via variable weight feature selection

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Modeling the impact of heat rejection from split air conditioner on outdoor air temperature in high-density residential areas

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A method to estimate leaf area index from VIIRS surface reflectance using deep transfer learning

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Adaptive Feature Selection for Probabilistic Multi-Energy Load Forecasting

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A Review of Industrial Load Flexibility Enhancement for Demand-Response Interaction

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Hourly Urban Water Demand Forecasting Using the Continuous Deep Belief Echo State Network

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Prediction model of the large commercial building cooling loads based on rough set and deep extreme learning machine

Lei, L., & Shao, S. (2023) · Journal of Building Engineering · doi:10.1016/j.jobe.2023.107958 · Cited by 23

Forecasting of solar radiation for a cleaner environment using robust machine learning techniques

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Multiple criteria assessment of methods for forecasting building thermal energy demand

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Statistical and Artificial Intelligence-Based Tools for Building Energy Prediction: A Systematic Literature Review

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Short-term prediction of photovoltaic power based on quadratic decomposition and residual correction

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An intelligent way to predict the building thermal needs: ANNs and optimization

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Modeling and predicting energy consumption of chiller based on dynamic spatial-temporal graph neural network

Liu, Q., Cheng, X., Jianzhong, S., Ma, Y., & Peng, P. (2024) · Journal of Building Engineering · doi:10.1016/j.jobe.2024.109657 · Cited by 19

BEForeGAN: An image-based deep generative approach for day-ahead forecasting of building HVAC energy consumption

Ma, Y. X., & Yeung, K. L. (2024) · Applied Energy · doi:10.1016/j.apenergy.2024.124196 · Cited by 20

A novel ensemble method for residential electricity demand forecasting based on a novel sample simulation strategy

Zhang, G., & Guo, J. (2020) · Energy · doi:10.1016/j.energy.2020.118265 · Cited by 18

Modeling of nitrogen solubility in unsaturated, cyclic, and aromatic hydrocarbons: Deep learning methods and SAFT equation of state

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Privileged information-driven random network based non-iterative integration model for building energy consumption prediction

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Empirical mode decomposition using deep learning model for financial market forecasting

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Estimating cooling production and monitoring efficiency in chillers using a soft sensor

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Eye State Identification Utilizing EEG Signals: A Combined Method Using Self-Organizing Map and Deep Belief Network

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A hybrid model based on multivariate fast iterative filtering and long short-term memory for ultra-short-term cooling load prediction

Myat, A., Namitha, K., Soh, Y. L., & An, H. (2024) · Energy and Buildings · doi:10.1016/j.enbuild.2024.113977 · Cited by 16

A Novel Interval Energy-Forecasting Method for Sustainable Building Management Based on Deep Learning

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Electricity demand uncertainty modeling with Temporal Convolution Neural Network models

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A Short-Term Building Load Prediction Method Based on Modal Decomposition and Deep Learning

Lu, S., Yu, D., Ding, Y. Y., Chen, W., Liang, C., Yuan, J., Tian, Z., & Lu, Y. (2025) · Buildings · doi:10.3390/buildings15244455 · Cited by 2

SPEHDSTCN: A statistical prior error-corrected heterogeneous depthwise separable temporal convolutional network for building air-conditioning cooling load forecasting

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TFDiFormer: A Hybrid Deep Learning Model for Airport Terminal Cooling Load ForecastingPreprint

Lin, R., Yuan, Z., Liu, T., Yu, L., Li, K., Xu, Y., & Wang, K. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5668722

A novel deep-learning framework for short-term prediction of cooling load in public buildings

Song, C., Yang, H., Meng, X.-B., Yang, P., Cai, J., Bao, H., & Xu, K. (2023) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2023.139796 · Cited by 40

Optimal load demand forecasting in air conditioning using deep belief networks optimized by an improved version of snake optimization algorithm

Jiang, H., Li, M., & Fathi, G. (2023) · IET Renewable Power Generation · doi:10.1049/rpg2.12819 · Cited by 10