Research graph
References from A hybrid model for predicting the operation status and power of residential air conditioning based on coupled indoor-outdoor hygrothermal variations. Local targets link to admitted publications; unresolved targets remain external evidence.
14. United Nations Environment Programme (UNEP)
10.1093/yiel/yvab060 · 2022 · External reference
The Future of Cooling: Opportunities for energy-efficient air conditioning
2018 · External reference
Indoor thermal environment and adaptive behaviors in summer of urban households in northern China: Status and trend
10.1016/j.enbuild.2024.114916 · 2024 · External reference
Seawater air-conditioning and ammonia district cooling: A solution for warm coastal regions
10.1016/j.energy.2022.124359 · 2022 · External reference
Climate Change 2021 – The Physical Science Basis
2023 · External reference
Unresolved reference
2021 · External reference
Dynamic rule-based change-over ventilation strategy with weather-responsive air-conditioning setpoints
10.1016/j.buildenv.2023.110966 · 2023 · External reference
A review on the basics of building energy estimation
10.1016/j.rser.2013.11.040 · 2014 · External reference
The impact of building operations on urban heat/cool islands under urban densification: A comparison between naturally-ventilated and air-conditioned buildings
10.1016/j.apenergy.2018.10.108 · 2019 · External reference
Mapping the city scale anthropogenic heat emissions from buildings in Kuala Lumpur through a top-down and a bottom-up approach
10.1016/j.scs.2021.103443 · 2022 · External reference
Impacts of urban microclimate on summertime sensible and latent energy demand for cooling in residential buildings of Hong Kong
10.1016/j.energy.2019.116208 · 2019 · External reference
Computer simulation of moisture transfer in walls: Impacts on the thermal performance of buildings
10.1080/17452007.2021.1916426 · 2022 · External reference
Real-time estimation of thermal comfort indices in an office building with a solar powered HVAC system
2015 · External reference
The Impact of Building Codes on HVAC Estimation: How Regulations Influence Cost and Design Choices
10.55041/ijsrem37469 · 2024 · External reference
How heat waves and urban microclimates affect building cooling energy demand? Insights from fifteen eastern Chinese cities
10.1016/j.apenergy.2025.125424 · 2025 · External reference
On the potential of building adaptation measures to counterbalance the impact of climatic change in the tropics
10.1016/j.enbuild.2020.110494 · 2020 · External reference
The International Urban Energy Balance Models Comparison Project: First Results from Phase 1
10.1175/2010jamc2354.1 · 2010 · External reference
Urban meteorological forcing data for building energy simulations
10.1016/j.buildenv.2021.108088 · 2021 · External reference
Identifying suitable models for the heat dynamics of buildings
10.1016/j.enbuild.2011.02.005 · 2011 · External reference
Quality of grey-box models and identified parameters as function of the accuracy of input and observation signals
10.1016/j.enbuild.2014.07.025 · 2014 · External reference
An Iterative Methodology for Model Complexity Reduction in Residential Building Simulation
10.3390/en12122448 · 2019 · External reference
Short-term electrical load forecasting using the Support Vector Regression (SVR) model to calculate the demand response baseline for office buildings
10.1016/j.apenergy.2017.03.034 · 2017 · External reference
Gradient boosting machine for modeling the energy consumption of commercial buildings
10.1016/j.enbuild.2017.11.039 · 2018 · External reference
Electricity Load Forecasting for Each Day of Week Using Deep CNN
2019 · External reference
A Short-Term Residential Load Forecasting Model Based on LSTM Recurrent Neural Network Considering Weather Features
10.3390/en14102737 · 2021 · External reference
Short-Term Load Forecasting for Commercial Building Using Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Network with Similar Day Selection Model
10.1007/s42835-023-01660-3 · 2023 · External reference
Deep spatio-temporal feature fusion learning for multi-step building cooling load forecasting
10.1016/j.enbuild.2024.114735 · 2024 · External reference
Hybrid forecasting model of building cooling load based on EMD-LSTM-Markov algorithm
10.1016/j.enbuild.2024.114670 · 2024 · External reference
Hybrid forecasting model of building cooling load based on combined neural network
10.1016/j.energy.2024.131317 · 2024 · External reference
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
10.1016/j.jcp.2018.10.045 · 2019 · External reference
Deep learning and transfer learning techniques applied to short-term load forecasting of data-poor buildings in local energy communities
10.1016/j.enbuild.2023.113164 · 2023 · External reference
Virtual metering of heat supplied by zone-level perimeter heaters: An investigation with three inverse modelling approaches
10.1016/j.enbuild.2021.110867 · 2021 · External reference
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
10.1109/access.2020.2970143 · 2020 · External reference
Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information
10.1016/j.apenergy.2024.124580 · 2025 · External reference
Non-intrusive thermal load disaggregation and forecasting for effective HVAC systems
10.1016/j.apenergy.2024.123379 · 2024 · External reference
A behavior-orientated prediction method for short-term energy consumption of air-conditioning systems in buildings blocks
10.1016/j.energy.2022.125940 · 2023 · External reference
Exploring occupant behaviors and interactions in buildings with energy-efficient renovations: A hybrid virtual-physical experimental approach
10.1016/j.buildenv.2024.111991 · 2024 · External reference
Energy efficiency and comfort: Analysis of thermal responses and behaviors of residents with high and low air conditioning dependency
10.1016/j.enbuild.2025.115695 · 2025 · External reference
Dynamic room temperature setpoints of air-conditioning demand response based on heat balance equations with thermal comfort model as constraint: On-site experiment and simulation
10.1016/j.jobe.2022.105798 · 2023 · External reference
Unresolved reference
2016 · External reference
Data-driven and physical model-based evaluation method for the achievable demand response potential of residential consumers’ air conditioning loads
10.1016/j.apenergy.2021.118017 · 2022 · External reference
Experimental study on flexible energy use feature of multi-split air-conditioning system with different control schemes in summer
10.1016/j.enbuild.2025.115875 · 2025 · External reference
Comparative research on different air conditioning systems for residential buildings
10.1016/j.foar.2016.11.004 · 2017 · External reference
Occupant behavior, thermal environment, and appliance electricity use of a single-family apartment in China
10.1038/s41597-023-02891-9 · 2024 · External reference
Regional climate effects on the optimal thermal resistance and capacitance of residential building walls
10.1016/j.enbuild.2021.111030 · 2021 · External reference
A global model of hourly space heating and cooling demand at multiple spatial scales
10.1038/s41560-023-01341-5 · 2023 · External reference
Evaluating single-zone grey-box thermal models: Impact of model structure on prediction accuracy and computational cost
10.1016/j.enbuild.2026.117139 · 2026 · External reference
Greedy function approximation: A gradient boosting machine
10.1214/aos/1013203451 · 2001 · External reference
Machine learning modeling using XGBoost and LightGBM for predicting the minimum ignition temperature of rice husk dust based on the synergistic effect of dispersion pressure and crushed brown rice
10.1016/j.powtec.2025.120682 · 2025 · External reference
Analysis of hydropower plant guide bearing vibrations by machine learning based identification of steady operations
10.1016/j.renene.2024.121463 · 2024 · External reference
Optimal Detection of Changepoints With a Linear Computational Cost
10.1080/01621459.2012.737745 · 2012 · External reference
Short-Term Load Forecasting for Commercial Building Using Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) Network with Similar Day Selection Model
10.1007/s42835-023-01660-3 · ExternalCitation · doi-reference
Short-term electrical load forecasting using the Support Vector Regression (SVR) model to calculate the demand response baseline for office buildings
10.1016/j.apenergy.2017.03.034 · ExternalCitation · doi-reference
The impact of building operations on urban heat/cool islands under urban densification: A comparison between naturally-ventilated and air-conditioned buildings
10.1016/j.apenergy.2018.10.108 · ExternalCitation · doi-reference
Data-driven and physical model-based evaluation method for the achievable demand response potential of residential consumers’ air conditioning loads
10.1016/j.apenergy.2021.118017 · ExternalCitation · doi-reference
Non-intrusive thermal load disaggregation and forecasting for effective HVAC systems
10.1016/j.apenergy.2024.123379 · ExternalCitation · doi-reference
Building electricity load forecasting based on spatiotemporal correlation and electricity consumption behavior information
10.1016/j.apenergy.2024.124580 · ExternalCitation · doi-reference
How heat waves and urban microclimates affect building cooling energy demand? Insights from fifteen eastern Chinese cities
10.1016/j.apenergy.2025.125424 · ExternalCitation · doi-reference
Urban meteorological forcing data for building energy simulations
10.1016/j.buildenv.2021.108088 · ExternalCitation · doi-reference
Dynamic rule-based change-over ventilation strategy with weather-responsive air-conditioning setpoints
10.1016/j.buildenv.2023.110966 · ExternalCitation · doi-reference
Exploring occupant behaviors and interactions in buildings with energy-efficient renovations: A hybrid virtual-physical experimental approach
10.1016/j.buildenv.2024.111991 · ExternalCitation · doi-reference
Identifying suitable models for the heat dynamics of buildings
10.1016/j.enbuild.2011.02.005 · ExternalCitation · doi-reference
Quality of grey-box models and identified parameters as function of the accuracy of input and observation signals
10.1016/j.enbuild.2014.07.025 · ExternalCitation · doi-reference
Gradient boosting machine for modeling the energy consumption of commercial buildings
10.1016/j.enbuild.2017.11.039 · ExternalCitation · doi-reference
On the potential of building adaptation measures to counterbalance the impact of climatic change in the tropics
10.1016/j.enbuild.2020.110494 · ExternalCitation · doi-reference
Virtual metering of heat supplied by zone-level perimeter heaters: An investigation with three inverse modelling approaches
10.1016/j.enbuild.2021.110867 · ExternalCitation · doi-reference
Regional climate effects on the optimal thermal resistance and capacitance of residential building walls
10.1016/j.enbuild.2021.111030 · ExternalCitation · doi-reference
Deep learning and transfer learning techniques applied to short-term load forecasting of data-poor buildings in local energy communities
10.1016/j.enbuild.2023.113164 · ExternalCitation · doi-reference
Hybrid forecasting model of building cooling load based on EMD-LSTM-Markov algorithm
10.1016/j.enbuild.2024.114670 · ExternalCitation · doi-reference
Deep spatio-temporal feature fusion learning for multi-step building cooling load forecasting
10.1016/j.enbuild.2024.114735 · ExternalCitation · doi-reference
Indoor thermal environment and adaptive behaviors in summer of urban households in northern China: Status and trend
10.1016/j.enbuild.2024.114916 · ExternalCitation · doi-reference
Energy efficiency and comfort: Analysis of thermal responses and behaviors of residents with high and low air conditioning dependency
10.1016/j.enbuild.2025.115695 · ExternalCitation · doi-reference
Experimental study on flexible energy use feature of multi-split air-conditioning system with different control schemes in summer
10.1016/j.enbuild.2025.115875 · ExternalCitation · doi-reference
Evaluating single-zone grey-box thermal models: Impact of model structure on prediction accuracy and computational cost
10.1016/j.enbuild.2026.117139 · ExternalCitation · doi-reference
Impacts of urban microclimate on summertime sensible and latent energy demand for cooling in residential buildings of Hong Kong
10.1016/j.energy.2019.116208 · ExternalCitation · doi-reference
Seawater air-conditioning and ammonia district cooling: A solution for warm coastal regions
10.1016/j.energy.2022.124359 · ExternalCitation · doi-reference
A behavior-orientated prediction method for short-term energy consumption of air-conditioning systems in buildings blocks
10.1016/j.energy.2022.125940 · ExternalCitation · doi-reference
Hybrid forecasting model of building cooling load based on combined neural network
10.1016/j.energy.2024.131317 · ExternalCitation · doi-reference
Comparative research on different air conditioning systems for residential buildings
10.1016/j.foar.2016.11.004 · ExternalCitation · doi-reference
Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
10.1016/j.jcp.2018.10.045 · ExternalCitation · doi-reference
Dynamic room temperature setpoints of air-conditioning demand response based on heat balance equations with thermal comfort model as constraint: On-site experiment and simulation
10.1016/j.jobe.2022.105798 · ExternalCitation · doi-reference
Machine learning modeling using XGBoost and LightGBM for predicting the minimum ignition temperature of rice husk dust based on the synergistic effect of dispersion pressure and crushed brown rice
10.1016/j.powtec.2025.120682 · ExternalCitation · doi-reference
Analysis of hydropower plant guide bearing vibrations by machine learning based identification of steady operations
10.1016/j.renene.2024.121463 · ExternalCitation · doi-reference
A review on the basics of building energy estimation
10.1016/j.rser.2013.11.040 · ExternalCitation · doi-reference
Mapping the city scale anthropogenic heat emissions from buildings in Kuala Lumpur through a top-down and a bottom-up approach
10.1016/j.scs.2021.103443 · ExternalCitation · doi-reference
A global model of hourly space heating and cooling demand at multiple spatial scales
10.1038/s41560-023-01341-5 · ExternalCitation · doi-reference
Occupant behavior, thermal environment, and appliance electricity use of a single-family apartment in China
10.1038/s41597-023-02891-9 · ExternalCitation · doi-reference
Optimal Detection of Changepoints With a Linear Computational Cost
10.1080/01621459.2012.737745 · ExternalCitation · doi-reference
Computer simulation of moisture transfer in walls: Impacts on the thermal performance of buildings
10.1080/17452007.2021.1916426 · ExternalCitation · doi-reference
14. United Nations Environment Programme (UNEP)
10.1093/yiel/yvab060 · ExternalCitation · doi-reference
Digital Twin: Values, Challenges and Enablers From a Modeling Perspective
10.1109/access.2020.2970143 · ExternalCitation · doi-reference
The International Urban Energy Balance Models Comparison Project: First Results from Phase 1
10.1175/2010jamc2354.1 · ExternalCitation · doi-reference
Greedy function approximation: A gradient boosting machine
10.1214/aos/1013203451 · ExternalCitation · doi-reference
An Iterative Methodology for Model Complexity Reduction in Residential Building Simulation
10.3390/en12122448 · ExternalCitation · doi-reference
A Short-Term Residential Load Forecasting Model Based on LSTM Recurrent Neural Network Considering Weather Features
10.3390/en14102737 · ExternalCitation · doi-reference
The Impact of Building Codes on HVAC Estimation: How Regulations Influence Cost and Design Choices
10.55041/ijsrem37469 · ExternalCitation · doi-reference
