相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Data-driven building energy modelling - An analysis of the potential for generalisation through interpretable machine learning
Massimiliano Manfren et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2022)
Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics
Giuseppe Pinto et al.
ENERGY AND BUILDINGS (2022)
Transfer learning for smart buildings: A critical review of algorithms, applications, and future perspectives
Giuseppe Pinto et al.
ADVANCES IN APPLIED ENERGY (2022)
A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings
Sadi Alawadi et al.
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS (2022)
Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency
Samir Touzani et al.
APPLIED ENERGY (2021)
An explainable one-dimensional convolutional neural networks based fault diagnosis method for building heating, ventilation and air conditioning systems
Guannan Li et al.
BUILDING AND ENVIRONMENT (2021)
Forecasting building occupancy: A temporal-sequential analysis and machine learning integrated approach
Jin Yuan et al.
ENERGY AND BUILDINGS (2021)
Data-driven building energy modeling with feature selection and active learning for data predictive control
Liang Zhang
ENERGY AND BUILDINGS (2021)
Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality
Nan Ma et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2021)
An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning
Xiangyu Zhang et al.
IEEE TRANSACTIONS ON SMART GRID (2021)
A review of machine learning in building load prediction
Liang Zhang et al.
APPLIED ENERGY (2021)
Experiment study of machine-learning-based approximate model predictive control for energy-efficient building control
Shiyu Yang et al.
APPLIED ENERGY (2021)
A Novel Machine Learning-Based Price Forecasting for Energy Management Systems
Adnan Yousaf et al.
SUSTAINABILITY (2021)
Demystifying Thermal Comfort in Smart Buildings: An Interpretable Machine Learning Approach
Wei Zhang et al.
IEEE INTERNET OF THINGS JOURNAL (2021)
Active learning strategy for high fidelity short-term data-driven building energy forecasting
Liang Zhang et al.
ENERGY AND BUILDINGS (2021)
Sensor impacts on building and HVAC controls: A critical review for building energy performance
Yeonjin Bae et al.
ADVANCES IN APPLIED ENERGY (2021)
Sensor impact evaluation and verification for fault detection and diagnostics in building energy systems: A review
Liang Zhang et al.
ADVANCES IN APPLIED ENERGY (2021)
A review of studies applying machine learning models to predict occupancy and window-opening behaviours in smart buildings
Xilei Dai et al.
ENERGY AND BUILDINGS (2020)
State-of-the-art on research and applications of machine learning in the building life cycle
Tianzhen Hong et al.
ENERGY AND BUILDINGS (2020)
A review on machine learning algorithms to predict daylighting inside buildings
Mohammed Ayoub
SOLAR ENERGY (2020)
A novel reinforcement learning method for improving occupant comfort via window opening and closing
Mengjie Han et al.
SUSTAINABLE CITIES AND SOCIETY (2020)
Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization
Shiyu Yang et al.
APPLIED ENERGY (2020)
Reinforcement learning for building controls: The opportunities and challenges
Zhe Wang et al.
APPLIED ENERGY (2020)
Air Temperature Forecasting Using Machine Learning Techniques: A Review
Jenny Cifuentes et al.
ENERGIES (2020)
Data-driven predictive models for residential building energy use based on the segregation of heating and cooling days
Ehsan Kamel et al.
ENERGY (2020)
Lighting system control techniques in commercial buildings: Current trends and future directions
Khairul Rijal Wagiman et al.
JOURNAL OF BUILDING ENGINEERING (2020)
A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings
Liang Zhang et al.
BUILDING AND ENVIRONMENT (2020)
Reinforcement Learning for Control of Building HVAC Systems
Naren Srivaths Raman et al.
2020 AMERICAN CONTROL CONFERENCE (ACC) (2020)
A novel methodology to explain and evaluate data-driven building energy performance models based on interpretable machine learning
Cheng Fan et al.
APPLIED ENERGY (2019)
Real time optimal control of district cooling system with thermal energy storage using neural networks
Sam J. Cox et al.
APPLIED ENERGY (2019)
Reinforcement learning for demand response: A review of algorithms and modeling techniques
Jose R. Vazquez-Canteli et al.
APPLIED ENERGY (2019)
Assessment of deep recurrent neural network-based strategies for short-term building energy predictions
Cheng Fan et al.
APPLIED ENERGY (2019)
Data fusion in predicting internal heat gains for office buildings through a deep learning approach
Zhe Wang et al.
APPLIED ENERGY (2019)
State of the Art of Machine Learning Models in Energy Systems, a Systematic Review
Amir Mosavi et al.
ENERGIES (2019)
Neural network, ARX, and extreme learning machine models for the short-term prediction of temperature in buildings
Primoz Potocnik et al.
BUILDING SIMULATION (2019)
Economic model predictive control for demand flexibility of a residential building
Christian Finck et al.
ENERGY (2019)
Machine learning and statistical models for predicting indoor air quality
Wenjuan Wei et al.
INDOOR AIR (2019)
A review of reinforcement learning for autonomous building energy management
Karl Mason et al.
COMPUTERS & ELECTRICAL ENGINEERING (2019)
Modeling and Optimizing a Chiller System Using a Machine Learning Algorithm
Jee-Heon Kim et al.
ENERGIES (2019)
Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
Zhiang Zhang et al.
ENERGY AND BUILDINGS (2019)
Machine learning vs. hybrid machine learning model for optimal operation of a chiller
Sungho Park et al.
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT (2019)
A review of reinforcement learning methodologies for controlling occupant comfort in buildings
Mengjie Han et al.
SUSTAINABLE CITIES AND SOCIETY (2019)
LightLearn: An adaptive and occupant centered controller for lighting based on reinforcement learning
June Young Park et al.
BUILDING AND ENVIRONMENT (2019)
Improving prediction performance for indoor temperature in public buildings based on a novel deep learning method
Chengliang Xu et al.
BUILDING AND ENVIRONMENT (2019)
A systematic feature selection procedure for short-term data-driven building energy forecasting model development
Liang Zhang et al.
ENERGY AND BUILDINGS (2019)
Critical review and research roadmap of office building energy management based on occupancy monitoring
Shide Salimi et al.
ENERGY AND BUILDINGS (2019)
Building HVAC Scheduling Using Reinforcement Learning via Neural Network Based Model Approximation
Chi Zhang et al.
BUILDSYS'19: PROCEEDINGS OF THE 6TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION (2019)
OCTOPUS: Deep Reinforcement Learning for Holistic Smart Building Control
Xianzhong Ding et al.
BUILDSYS'19: PROCEEDINGS OF THE 6TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION (2019)
Gnu-RL: A Precocial Reinforcement Learning Solution for Building HVAC Control Using a Differentiable MPC Policy
Bingqing Chen et al.
BUILDSYS'19: PROCEEDINGS OF THE 6TH ACM INTERNATIONAL CONFERENCE ON SYSTEMS FOR ENERGY-EFFICIENT BUILDINGS, CITIES, AND TRANSPORTATION (2019)
Reinforcement Learning for Mixing Loop Control with Flow Variable Eligibility Trace
Anders Overgaard et al.
2019 3RD IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (IEEE CCTA 2019) (2019)
Data-driven model predictive control using random forests for building energy optimization and climate control
Francesco Smarra et al.
APPLIED ENERGY (2018)
Machine learning-based thermal response time ahead energy demand prediction for building heating systems
Yabin Guo et al.
APPLIED ENERGY (2018)
Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems
Hussain Kazmi et al.
ENERGY (2018)
Assessment of indoor illuminance and study on best photosensors' position for design and commissioning of Daylight Linked Control systems. A new method based on artificial neural networks
M. Beccali et al.
ENERGY (2018)
Optimal control of HVAC and window systems for natural ventilation through reinforcement learning
Yujiao Chen et al.
ENERGY AND BUILDINGS (2018)
Activity-aware HVAC power demand forecasting
Enric Sala-Cardoso et al.
ENERGY AND BUILDINGS (2018)
Short term predictions of occupancy in commercial buildings-Performance analysis for stochastic models and machine learning approaches
Zhaoxuan Li et al.
ENERGY AND BUILDINGS (2018)
Building occupancy modeling using generative adversarial network
Zhenghua Chen et al.
ENERGY AND BUILDINGS (2018)
Using an ensemble machine learning methodology-Bagging to predict occupants' thermal comfort in buildings
Zhibin Wu et al.
ENERGY AND BUILDINGS (2018)
Modeling techniques used in building HVAC control systems: A review
Zakia Afroz et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2018)
Practical Implementation and Evaluation of Deep Reinforcement Learning Control for a Radiant Heating System
Zhiang Zhang et al.
BUILDSYS'18: PROCEEDINGS OF THE 5TH CONFERENCE ON SYSTEMS FOR BUILT ENVIRONMENTS (2018)
A novel fuzzy control algorithm for reducing the peak demands using energy storage system
Kein Huat Chua et al.
ENERGY (2017)
An energy-efficient predictive control for HVAC systems applied to tertiary buildings based on regression techniques
Diana Manjarres et al.
ENERGY AND BUILDINGS (2017)
Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption
Muhammad Waseem Ahmad et al.
ENERGY AND BUILDINGS (2017)
Model Predictive Control-Based Optimal Operations of District Heating System With Thermal Energy Storage and Flexible Loads
Francesca Verrilli et al.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2017)
A review and analysis of regression and machine learning models on commercial building electricity load forecasting
B. Yildiz et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2017)
Residential Demand Response of Thermostatically Controlled Loads Using Batch Reinforcement Learning
Frederik Ruelens et al.
IEEE TRANSACTIONS ON SMART GRID (2017)
Deep Reinforcement Learning for Building HVAC Control
Tianshu Wei et al.
PROCEEDINGS OF THE 2017 54TH ACM/EDAC/IEEE DESIGN AUTOMATION CONFERENCE (DAC) (2017)
Short-term residential load forecasting: Impact of calendar effects and forecast granularity
Peter Lusis et al.
APPLIED ENERGY (2017)
A short-term building cooling load prediction method using deep learning algorithms
Cheng Fan et al.
APPLIED ENERGY (2017)
Development of a probabilistic graphical model for predicting building energy performance
Zheng O'Neill et al.
APPLIED ENERGY (2016)
Simulation-based optimization of an integrated daylighting and HVAC system using the design of experiments method
Wonuk Kim et al.
APPLIED ENERGY (2016)
Short-term building energy model recommendation system: A meta-learning approach
Can Cui et al.
APPLIED ENERGY (2016)
A novel optimization algorithm based on epsilon constraint-RBF neural network for tuning PID controller in decoupled HVAC system
Seyed Mohammad Attaran et al.
APPLIED THERMAL ENGINEERING (2016)
Development of an occupancy prediction model using indoor environmental data based on machine learning techniques
Seung Ho Ryu et al.
BUILDING AND ENVIRONMENT (2016)
Application of artificial neural network for predicting hourly indoor air temperature and relative humidity in modern building in humid region
Leopold Mba et al.
ENERGY AND BUILDINGS (2016)
Applied machine learning: Forecasting heat load in district heating system
Samuel Idowu et al.
ENERGY AND BUILDINGS (2016)
Design and development of advanced fuzzy logic controllers in smart buildings for institutional buildings in subtropical Queensland
Yazeed Yasin Ghadi et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2016)
Computational intelligence techniques for HVAC systems: A review
Muhammad Waseem Ahmad et al.
BUILDING SIMULATION (2016)
Experimental analysis of data-driven control for a building heating system
G. T. Costanzo et al.
SUSTAINABLE ENERGY GRIDS & NETWORKS (2016)
PVM-based intelligent predictive control of HVAC systems
A. Ruano et al.
IFAC PAPERSONLINE (2016)
Reinforcement learning for optimal control of low exergy buildings
Lei Yang et al.
APPLIED ENERGY (2015)
MPC control for improving energy efficiency of a building air handler for multi-zone VAVs
Wei Liang et al.
BUILDING AND ENVIRONMENT (2015)
A new model predictive control scheme for energy and cost savings in commercial buildings: An airport terminal building case study
Hao Huang et al.
BUILDING AND ENVIRONMENT (2015)
Multi-objective optimization of the HVAC (heating, ventilation, and air conditioning) system performance
Xiupeng Wei et al.
ENERGY (2015)
A neural network-based multi-zone modelling approach for predictive control system design in commercial buildings
Hao Huang et al.
ENERGY AND BUILDINGS (2015)
Building optimization and control algorithms implemented in existing BEMS using a web based energy management and control system
Sotiris Papantoniou et al.
ENERGY AND BUILDINGS (2015)
Machine learning: Trends, perspectives, and prospects
M. I. Jordan et al.
SCIENCE (2015)
Optimal Self-Tuning PID Controller Based on Low Power Consumption for a Server Fan Cooling System
Chengming Lee et al.
SENSORS (2015)
Learning Optimization Friendly Comfort Model for HVAC Model Predictive Control
Yuxun Zhou et al.
2015 IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOP (ICDMW) (2015)
Optimal HVAC control as demand response with on-site energy storage and generation system
Young M. Lee et al.
6TH INTERNATIONAL BUILDING PHYSICS CONFERENCE (IBPC 2015) (2015)
Autonomous HVAC Control, A Reinforcement Learning Approach
Enda Barrett et al.
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, PT III (2015)
Accurately predicting building energy performance using evolutionary multivariate adaptive regression splines
Min-Yuan Cheng et al.
APPLIED SOFT COMPUTING (2014)
Model predictive control: Recent developments and future promise
David Q. Mayne
AUTOMATICA (2014)
Comfort-based fuzzy control optimization for energy conservation in HVAC systems
Sajid Hussain et al.
CONTROL ENGINEERING PRACTICE (2014)
A Dynamic Fuzzy Controller to Meet Thermal Comfort by Using Neural Network Forecasted Parameters as the Input
Mario Collotta et al.
ENERGIES (2014)
Modeling and short-term prediction of HVAC system with a clustering algorithm
Fan Tang et al.
ENERGY AND BUILDINGS (2014)
Development of an energy prediction tool for commercial buildings using case-based reasoning
Danielle Monfet et al.
ENERGY AND BUILDINGS (2014)
Reduced-order residential home modeling for model predictive control
Wesley J. Cole et al.
ENERGY AND BUILDINGS (2014)
A Model Predictive Control Approach to Microgrid Operation Optimization
Alessandra Parisio et al.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY (2014)
Low computational cost technique for predictive management of thermal comfort in non-residential buildings
Antoine Garnier et al.
JOURNAL OF PROCESS CONTROL (2014)
Optimisation of energy management in commercial buildings with weather forecasting inputs: A review
Dimitris Lazos et al.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS (2014)
A systematic approach to occupancy modeling in ambient sensor-rich buildings
Zheng Yang et al.
SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL (2014)
A real-time model predictive control for building heating and cooling systems based on the occupancy behavior pattern detection and local weather forecasting
Bing Dong et al.
BUILDING SIMULATION (2014)
Using reinforcement learning to optimize occupant comfort and energy usage in HVAC systems
Pedro Fazenda et al.
JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS (2014)
Building operation and energy performance: Monitoring, analysis and optimisation toolkit
Andrea Costa et al.
APPLIED ENERGY (2013)
Multi-objective optimization of indoor air quality control and energy consumption minimization in a subway ventilation system
Hongbin Liu et al.
ENERGY AND BUILDINGS (2013)
Energy analysis of a building using artificial neural network: A review
Rajesh Kumar et al.
ENERGY AND BUILDINGS (2013)
Application of machine learning in the fault diagnostics of air handling units
Massieh Najafi et al.
APPLIED ENERGY (2012)
Demand reduction in building energy systems based on economic model predictive control
Jingran Ma et al.
CHEMICAL ENGINEERING SCIENCE (2012)
Use of model predictive control and weather forecasts for energy efficient building climate control
Frauke Oldewurtel et al.
ENERGY AND BUILDINGS (2012)
Illuminance-based slat angle selection model for automated control of split blinds
Jia Hu et al.
BUILDING AND ENVIRONMENT (2011)
Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural network models for an open office
G. Mustafaraj et al.
ENERGY AND BUILDINGS (2011)
A study of the importance of occupancy to building cooling load in prediction by intelligent approach
Simon S. K. Kwok et al.
ENERGY CONVERSION AND MANAGEMENT (2011)
Advanced control strategies for HVACR systemsAn overview: Part II: Soft and fusion control
D. Subbaram Naidu et al.
HVAC&R RESEARCH (2011)
Online tuning of a supervisory fuzzy controller for low-energy building system using reinforcement learning
Zhen Yu et al.
CONTROL ENGINEERING PRACTICE (2010)
A decision tree method for building energy demand modeling
Zhun Yu et al.
ENERGY AND BUILDINGS (2010)
Comparison of Short-Term Weather Forecasting Models for Model Predictive Control
Anthony R. Florita et al.
HVAC&R RESEARCH (2009)
Artificial neural networks and adaptive neuro-fuzzy assessments for ground-coupled heat pump system
Hikmet Esen et al.
ENERGY AND BUILDINGS (2008)
Performance prediction of a cooling tower using artificial neural network
M. Hosoz et al.
ENERGY CONVERSION AND MANAGEMENT (2007)
Experimental analysis of simulated reinforcement learning control for active and passive building thermal storage inventory Part 2: Results and analysis
SM Liu et al.
ENERGY AND BUILDINGS (2006)
Global optimization of absorption chiller system by genetic algorithm and neural network
TT Chow et al.
ENERGY AND BUILDINGS (2002)
Modelling of vapour-compression liquid chillers with neural networks
DJ Swider et al.
APPLIED THERMAL ENGINEERING (2001)
分享论文
