[1]
Kolokotsa, D. et al (2002), Genetic algorithms optimized fuzzy controller for the indoor environmental management in buildings implemented using PLC and local operating networks, Engineering Applications of Artificial Intelligence, 15(5): 417-428.
DOI: 10.1016/s0952-1976(02)00090-8
Google Scholar
[2]
Rui Yang and Lingfeng Wang (2010), Multi-objective optimization for decision-making of energy and comfort management in building automation and control, Sustainable Cities and Society, 2(1): 1– 7.
DOI: 10.1016/j.scs.2011.09.001
Google Scholar
[3]
Alonso, J. M et al (1998).
Google Scholar
[4]
Fanger, P.O. (1970), Thermal Comfort Analysis and Applications in Environmental Engineering. New York: McGraw-Hill.
Google Scholar
[5]
Ari, S. et al (2006), Fuzzy Logic and Neural Network Approximation to Indoor Comfort and Energy Optimization, 2006 Annual meeting of the North American Fuzzy Information Processing Society, 3-6 June, Montreal: IEEE, 692 – 695.
DOI: 10.1109/nafips.2006.365493
Google Scholar
[6]
Ma Bingxin et al (2011), Experimental Design and the GA-BP Prediction of Human Thermal Comfort Index, 2011 Seventh International Conference onNatural Computation (ICNC), 26-28 July, Shanghai: IEEE, 771-775.
DOI: 10.1109/icnc.2011.6022146
Google Scholar
[7]
Baker, N. et al (1993), Daylight in Architecture, a European Reference Handbook, UK: James & James.
Google Scholar
[8]
Hui Xie et al (2009), Prediction of Indoor Air Quality Using Artificial Neural Networks, 2009 Fifth International Conference on Natural Computation, 14-16 August, Tianjin: IEEE, 414 – 418.
DOI: 10.1109/icnc.2009.502
Google Scholar