Predicting moisture condensation risk on the radiant cooling floor of an office using integration of a genetic algorithm-back-propagation neural network with sensitivity analysis

Predicting moisture condensation risk on the radiant cooling floor of an office using integration of a genetic algorithm-back-propagation neural network with sensitivity analysis

Pre-dehumidification time (τpre) and pre-dehumidification energy consumption (Epre) play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling (RFC) system. However, there are few theoretical or experimental studies that focus on these two...

Full description

Bibliographic Details
Main Authors: Meng Su, Jiying Liu, Moon Keun Kim, Xiaozhou Wu
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-02-01
Series:Energy and Built Environment
Subjects:
Condensation prevention
Radiant floor cooling
Ventilation system
genetic algorithm
BP neural network
Online Access:http://www.sciencedirect.com/science/article/pii/S2666123322000642

Similar Items

Similar Items