Reprint
Application of Data-Driven Method for HVAC System
Edited by
December 2023
272 pages
- ISBN978-3-0365-9691-4 (Hardback)
- ISBN978-3-0365-9690-7 (PDF)
This book is a reprint of the Special Issue Application of Data-Driven Method for HVAC System that was published in
Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
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.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
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; thermal environment; indoor air quality; 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; temperature; relative humidity; CO concentration; CO2 concentration; cooking procedure; n/a