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Application of Data-Driven Method for HVAC System

This reprint, entitled “Application of data-driven method for HVAC System”, is dedicated to providing an overview of the latest achievements in the application of data-driven methods for HVAC systems. Topics of interest include, but are not limited to, the following: fault detection and diagnosis of...

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Format: Online
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2024
Subjects:
indoor air quality
high occupancy rate
natural ventilation
university building
intelligent packaging
temperature
humidity
supply chain
food waste
food quality
food preservation
transportation
grain bin
PCM
phase change temperature
energy saving
PCM latent heat
mobile public toilets
thermal environment
public health security
mechanical ventilation
aerosol transmission risk
underground commercial buildings
field measurement
air distribution optimization
M-cycle
evaporative cooling
solid desiccant
humidification–dehumidification desalination
water production
load data analysis
demand side management (DSM)
rural home hotels
cluster control strategy
PCM storage
air conditioning system
pattern recognition
clustering
correlation analysis
defrosting operation mode
low-carbon substation
climate zones
envelope thermal design
window to wall ratio
shape factor
chillers
fault diagnosis
fusion
residual
data
air-conditioned bed system
heat conduction heating
convection heating
thermal comfort
energy conservation
genetic algorithm
existing office parks
whole life cycle
cost benefits
carbon reduction
retrofit
relative humidity
CO concentration
CO2 concentration
cooking procedure
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thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
Online Access:ONIX_20240108_9783036596914_86
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Summary:This reprint, entitled “Application of data-driven method for HVAC System”, is dedicated to providing an overview of the latest achievements in the application of data-driven methods for HVAC systems. Topics of interest include, but are not limited to, the following: fault detection and diagnosis of HVAC systems; energy consumption prediction; model predictive control; data mining and analysis of HVAC systems; data mining and analysis of building environment; energy conservation; energy saving.

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