Application of machine learning in thermal comfort studies: A review of methods, performance and challenges

Optimization of thermal comfort, indoor quality, and energy-saving in campus classroom through deep Q learning

(2021) Kuan-Heng Yu et al.   Case Studies in Thermal Engineering

Adaptive behavior and different thermal experiences of real people: A Bayesian neural network approach to thermal preference prediction and classification

(2021) Nan Ma et al.   BUILDING AND ENVIRONMENT

Study on an adaptive thermal comfort model with K-nearest-neighbors (KNN) algorithm

(2021) Lei Xiong et al.   BUILDING AND ENVIRONMENT

Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles

(2021) Zeyu Wang et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

BIM and Data-Driven Predictive Analysis of Optimum Thermal Comfort for Indoor Environment

(2021) Vincent J.L. Gan et al.   SENSORS

An IoT-based deep learning approach to analyse indoor thermal comfort of disabled people

(2021) Bouziane Brik et al.   BUILDING AND ENVIRONMENT

Dynamic thermal perception: A review and agenda for future experimental research

(2021) Marika Vellei et al.   BUILDING AND ENVIRONMENT

Data-driven thermal comfort model via support vector machine algorithms: Insights from ASHRAE RP-884 database

(2020) Xiang Zhou et al.   ENERGY AND BUILDINGS

The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls

(2020) Jack Ngarambe et al.   ENERGY AND BUILDINGS

Comparing machine learning algorithms in predicting thermal sensation using ASHRAE Comfort Database II

(2020) Maohui Luo et al.   ENERGY AND BUILDINGS

Machine learning algorithms applied to a prediction of personal overall thermal comfort using skin temperatures and occupants' heating behavior

(2020) Katarina Katić et al.   APPLIED ERGONOMICS

A review of adaptive thermal comfort research since 1998

(2020) R. de Dear et al.   ENERGY AND BUILDINGS

Rethinking indoor thermal comfort in the era of rebound and pre‐bound effect for the developing world: A systematic review

(2020) Jeetika Malik et al.   INDOOR AIR

Evaluation of the Visual Stimuli on Personal Thermal Comfort Perception in Real and Virtual Environments Using Machine Learning Approaches

(2020) Francesco Salamone et al.   SENSORS

A review on machine learning algorithms to predict daylighting inside buildings

(2020) Mohammed Ayoub   SOLAR ENERGY

A novel reinforcement learning method for improving occupant comfort via window opening and closing

(2020) Mengjie Han et al.   Sustainable Cities and Society

Model predictive control with adaptive machine-learning-based model for building energy efficiency and comfort optimization

(2020) Shiyu Yang et al.   APPLIED ENERGY

A PMV-based HVAC control strategy for office rooms subjected to solar radiation

(2020) Jing Wu et al.   BUILDING AND ENVIRONMENT

Assessing occupants’ personal attributes in relation to human perception of environmental comfort: Measurement procedure and data analysis

(2020) Ilaria Pigliautile et al.   BUILDING AND ENVIRONMENT

Using machine learning algorithms to predict occupants’ thermal comfort in naturally ventilated residential buildings

(2020) Qian Chai et al.   ENERGY AND BUILDINGS

Review on occupant-centric thermal comfort sensing, predicting, and controlling

(2020) Jiaqing Xie et al.   ENERGY AND BUILDINGS

A machine learning approach to predict outdoor thermal comfort using local skin temperatures

(2020) Kuixing Liu et al.   Sustainable Cities and Society

Artificial Neural Network for the Thermal Comfort Index Prediction: Development of a New Simplified Algorithm

(2020) Domenico Palladino et al.   Energies

Efficient PMV computation for public environments with transient populations

(2020) Naji Sirhan et al.   ENERGY AND BUILDINGS

Improved long-term thermal comfort indices for continuous monitoring

(2020) Peixian Li et al.   ENERGY AND BUILDINGS

Supervised machine learning of thermal comfort under different indoor temperatures using EEG measurements

(2020) Xin Shan et al.   ENERGY AND BUILDINGS

PersonalisedComfort: a personalised thermal comfort model to predict thermal sensation votes for smart building residents

(2020) Saif Ur Rehman et al.   Enterprise Information Systems

Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality

(2020) Nan Ma et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

An investigation of indoor thermal environment in semi-cold region in Japan – Validity of thermal predictive indices in Nagano during the summer season

(2020) Hiroki Ikeda et al.   Journal of Building Engineering

Accuracy analyses and model comparison of machine learning adopted in building energy consumption prediction

(2019) Zhijian Liu et al.   ENERGY EXPLORATION & EXPLOITATION

Data-driven simulation of a thermal comfort-based temperature set-point control with ASHRAE RP884

(2019) Siliang Lu et al.   BUILDING AND ENVIRONMENT

The Squeaky wheel: Machine learning for anomaly detection in subjective thermal comfort votes

(2019) Zhe Wang et al.   BUILDING AND ENVIRONMENT

Temperature-preference learning with neural networks for occupant-centric building indoor climate controls

(2019) Yuzhen Peng et al.   BUILDING AND ENVIRONMENT

Energy optimization associated with thermal comfort and indoor air control via a deep reinforcement learning algorithm

(2019) William Valladares et al.   BUILDING AND ENVIRONMENT

Analysis of the accuracy on PMV – PPD model using the ASHRAE Global Thermal Comfort Database II

(2019) Toby Cheung et al.   BUILDING AND ENVIRONMENT

Quantification of personal thermal comfort with localized airflow system based on sensitivity analysis and classification tree model

(2019) Chenqiu Du et al.   ENERGY AND BUILDINGS

A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings

(2019) Tanaya Chaudhuri et al.   APPLIED ENERGY

Predicting older people's thermal sensation in building environment through a machine learning approach: Modelling, interpretation, and application

(2019) Zi Wang et al.   BUILDING AND ENVIRONMENT

Comparison of machine learning models for occupancy prediction in residential buildings using connected thermostat data

(2019) Brent Huchuk et al.   BUILDING AND ENVIRONMENT

Personal thermal comfort models with wearable sensors

(2019) Shichao Liu et al.   BUILDING AND ENVIRONMENT

A Framework for Adopting Adaptive Thermal Comfort Principles in Design and Operation of Buildings

(2019) Runa T. Hellwig et al.   ENERGY AND BUILDINGS

Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling

(2019) Wooyoung Jung et al.   SENSORS

Learning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States

(2019) Zhe Wang et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A review of reinforcement learning methodologies for controlling occupant comfort in buildings

(2019) Mengjie Han et al.   Sustainable Cities and Society

Towards non-intrusive and high accuracy prediction of personal thermal comfort using a few sensitive physiological parameters

(2019) Chengcheng Shan et al.   ENERGY AND BUILDINGS

Dimension analysis of subjective thermal comfort metrics based on ASHRAE Global Thermal Comfort Database using machine learning

(2019) Zhe Wang et al.   Journal of Building Engineering

Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control

(2018) Joyce Kim et al.   BUILDING AND ENVIRONMENT

Development of the ASHRAE Global Thermal Comfort Database II

(2018) Veronika Földváry Ličina et al.   BUILDING AND ENVIRONMENT

Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning

(2018) Joyce Kim et al.   BUILDING AND ENVIRONMENT

Random forest based thermal comfort prediction from gender-specific physiological parameters using wearable sensing technology

(2018) Tanaya Chaudhuri et al.   ENERGY AND BUILDINGS

Thermal comfort prediction using normalized skin temperature in a uniform built environment

(2018) Tanaya Chaudhuri et al.   ENERGY AND BUILDINGS

Artificial neural network models using thermal sensations and occupants’ behavior for predicting thermal comfort

(2018) Zhipeng Deng et al.   ENERGY AND BUILDINGS

Indoor environment quality assessment in classrooms: An integrated approach

(2018) Mohammad Tahsildoost et al.   Journal of Building Physics

Integrated Method for Personal Thermal Comfort Assessment and Optimization through Users’ Feedback, IoT and Machine Learning: A Case Study †

(2018) Francesco Salamone et al.   SENSORS

iTCM: Towards Learning-Based Thermal Comfort Modeling via Pervasive Sensing for Smart Buildings

(2018)   IEEE Internet of Things Journal

Machine learning method for real-time non-invasive prediction of individual thermal preference in transient conditions

(2018) Andrei Claudiu Cosma et al.   BUILDING AND ENVIRONMENT

Feature selection and Gaussian Process regression for personalized thermal comfort prediction

(2018) Janine Guenther et al.   BUILDING AND ENVIRONMENT

Learning desk fan usage preferences for personalised thermal comfort in shared offices using tree-based methods

(2018) Sindhu S. Shetty et al.   BUILDING AND ENVIRONMENT

Balancing indoor thermal comfort and energy consumption of ACMV systems via sparse swarm algorithms in optimizations

(2017) Deqing Zhai et al.   ENERGY AND BUILDINGS

A review of comfort, health, and energy use: Understanding daily energy use and wellbeing for the development of a new approach to study comfort

(2017) Marco A. Ortiz et al.   ENERGY AND BUILDINGS

A review of thermal comfort models and indicators for indoor environments

(2017) Diana Enescu   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

(2016) Lai Jiang et al.   BUILDING AND ENVIRONMENT

A systematic extreme learning machine approach to analyze visitors׳ thermal comfort at a public urban space

(2016) Shahab Kariminia et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Management and estimation of thermal comfort, carbon dioxide emission and economic growth by support vector machine

(2016) Igor Mladenović et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

A field study of thermal comfort for kindergarten children in Korea: An assessment of existing models and preferences of children

(2014) Hyunjun Yun et al.   BUILDING AND ENVIRONMENT