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Personal Comfort Centered Control with Random Forests and Deep Reinforcement Learning

https://doi.org/10.2139/ssrn.5450120
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inferredcites →https://doi.org/10.1016/j.apergo.2010.04.003openalex-snapshot
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All you need to know about model predictive control for buildings
inferredcites →https://doi.org/10.1016/j.buildenv.2009.06.022openalex-snapshot
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inferredcites →https://doi.org/10.1016/j.buildenv.2012.08.024openalex-snapshot
Dynamic predictive clothing insulation models based on outdoor air and indoor operative temperatures
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Personal comfort models: Predicting individuals' thermal preference using occupant heating and cooling behavior and machine learning
inferredcites →https://doi.org/10.1016/j.buildenv.2018.01.023openalex-snapshot
Personal comfort models – A new paradigm in thermal comfort for occupant-centric environmental control
inferredcites →https://doi.org/10.1016/j.buildenv.2019.106223openalex-snapshot
A comparative study of predicting individual thermal sensation and satisfaction using wrist-worn temperature sensor, thermal camera and ambient temperature sensor
inferredcites →https://doi.org/10.1016/j.buildenv.2019.106281openalex-snapshot
Personal thermal comfort models with wearable sensors
inferredcites →https://doi.org/10.1016/j.buildenv.2019.106351openalex-snapshot
A critical review of field implementations of occupant-centric building controls
inferredcites →https://doi.org/10.1016/j.conengprac.2019.104211openalex-snapshot
Data-driven methods for building control — A review and promising future directions
inferredcites →https://doi.org/10.1016/j.egypro.2019.01.494openalex-snapshot
Advanced Building Control via Deep Reinforcement Learning
inferredcites →https://doi.org/10.1016/j.enbuild.2010.09.001openalex-snapshot
Quantitative measurement of productivity loss due to thermal discomfort
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Model predictive control of a building heating system: The first experience
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An occupant-centric control strategy for indoor thermal comfort, air quality and energy management
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Energy-efficient control of indoor PM2.5 and thermal comfort in a real room using deep reinforcement learning
inferredcites →https://doi.org/10.1016/j.enbuild.2023.113770openalex-snapshot
Enhancing HVAC energy management through multi-zone occupant-centric approach: A multi-agent deep reinforcement learning solution
inferredcites →https://doi.org/10.1016/j.enpol.2011.09.003openalex-snapshot
Health and thermal comfort: From WHO guidance to housing strategies
inferredcites →https://doi.org/10.1016/j.jobe.2020.101714openalex-snapshot
Measurement of CO2 concentration for occupancy estimation in educational buildings with energy efficiency purposes
inferredcites →https://doi.org/10.1016/s0378-7788(02)00004-xopenalex-snapshot
Introduction to thermal comfort standards and to the proposed new version of EN ISO 7730
inferredcites →https://doi.org/10.1016/s0378-7788(02)00005-1openalex-snapshot
Thermal comfort in naturally ventilated buildings: revisions to ASHRAE Standard 55
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Adaptive thermal comfort and sustainable thermal standards for buildings
inferredcites →https://doi.org/10.1038/sj.jea.7500165openalex-snapshot
The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants
inferredcites →https://doi.org/10.1080/17512549.2018.1505654openalex-snapshot
On the interaction between personal comfort systems and centralized HVAC systems in office buildings
inferredcites →https://doi.org/10.1088/1742-6596/2042/1/012004openalex-snapshot
Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies
inferredcites →https://doi.org/10.1109/icdar.1995.598994openalex-snapshot
Random decision forests
inferredcites →https://doi.org/10.1145/3061639.3062224openalex-snapshot
Deep Reinforcement Learning for Building HVAC Control
inferredcites →https://doi.org/10.3182/20050703-6-cz-1902.01397openalex-snapshot
A SURVEY OF CONTROL TECHNOLOGIES IN THE BUILDING AUTOMATION INDUSTRY
inferredcites →https://doi.org/10.3390/buildings10100174openalex-snapshot
Humans-as-a-Sensor for Buildings—Intensive Longitudinal Indoor Comfort Models
inferredcites →https://doi.org/10.3390/en11030631openalex-snapshot
Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities
inferredcites →https://doi.org/10.48550/arxiv.1509.02971openalex-snapshot
Continuous control with deep reinforcement learning
inferredcites →https://doi.org/10.5555/1953048.2078195openalex-snapshot
Scikit-learn: Machine Learning in Python
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