Title :
Study on Thermal Comfort Control Based on Artificial Neural Network
Author :
Zhang Chun-Cheng ; Chen Xiang-guang
Author_Institution :
Sch. of Chem. Eng. & Environ., Beijing Inst. of Technol., Beijing, China
Abstract :
In order to investigate control method for indoor thermal comfort, the experimental environment of indoor thermal comfort is designed in this paper. Thermal comfort data are collected based on questionnaire means, ANN (artifical neural network) is trained using the data, and the ANN model trained can accurately forecast thermal comfort index. Relevant input parameters is conversely computed based on fixed network output, optimum control parameters in indoor air-condition can be obtained in order to achieve desired control index. The experiment results indicate that the control method proposed synthetically considers the effect on thermal comfort owing to indoor air temperature, outdoor air temperature and clothing case. Therefore, the forecast precision for thermal comfort is improved and indoor personnel´s requirement to thermal comfort can be satisfied.
Keywords :
air conditioning; neural nets; optimal control; temperature control; air temperature; artificial neural network; fixed network output; forecast precision; indoor air-condition; optimum control; optimum control parameter; thermal comfort control; thermal comfort index; Artificial neural networks; Chemical engineering; Educational institutions; Indexes; Meteorology; Temperature control; Thermal engineering;
Conference_Titel :
E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
Conference_Location :
Henan
Print_ISBN :
978-1-4244-7159-1
DOI :
10.1109/ICEEE.2010.5661189