-
[1] Ahn J., Cho S. Chung D. H. Analysis of energy and control efficiencies of fuzzy logic and artificial neural networks technologies in the heating energy supply system responding to the changes of user demands. Applied Energy 190, 2017, p. 222-231. DOI: 10.1016/j.apenergy.2016.12.155.
-
[2] Aleksiejuk P: Model prognostyczny zapotrzebowania na ciepło z wykorzystaniem struktur sztucznych sieci neuronowych. Instal, 2, 2016, s. 13-15.
-
[3] Alibabei N., Fung A. S., Raahemifar K., Moghimi A. Effects of intelligent strategy planning models on residential HVAC system energy demand and cost during the healing and cooling seasons. Applied Energy 185, 2017, p. 29-43. DOI: 10.1016/j.apenergy.2016.10.062 0306-2619.
-
[4] Al-Shammari E. I., Keivani K., Shamshirband S., Mostafaeipour A., Yee P. L., Pełkovic D., Ch. S. Prediction of heal load in district heating systems by Support Vector Machine with Firefly searching algorithm. Energy 95, 2016, p. 266-273. DOI: 10.1016/j.energy.2015.11.079.
-
[5] Balas P., Falba Ł. Inteligentna Sieć Ciepłownicza w Warszawie - charakterystyka projektu modernizacji Warszawskiej Sieci Ciepłowniczej. Instal 1, 2016, p. 5-10.
-
[6] Chou J.-S., Bui D.-K. Modeling cooling and heating loads by artificial intelligence for energy-efficient building design. Energy and Buildings 82, 2014, p. 437-446. DOI: 10.1016/j.enbuild.2014.07.036.
-
[7] Figueiredo J., Sa da Costa J. A SCADA system for energy management in intelligent buildings. Energy and Buildings 49, 2012, p. 85-98. DOI: 10.1016/j.enbuild.2012.01.041.
-
[8] Lilis G., Conus G., Asadi N., Kayal M. Towards the next generation of intelligent building: An assessment study of current automation and future loT based system with a proposal (or transitional design. Sustainable Cities and Society 28, 2017, p. 473-481. DOI: 10.1016/j.scs.2016.08.019.
-
[9] Mba L., Meukam P., Kemajou A. Application of artificial neural network for prediction hourly indoor air temperature and relative humidity in modem building in humid region. Energy and Buildings 121, 2016, p. 32-42. DOI: 10.1016/j.enbuild.2016.03.046.
-
[10] Medved S., Babnik M., Vidrih B., Arkar C. Parametric study on the advantages of weather-predicted control algorithm of free cooling ventilation system. Energy 73, 2014, p. 80-87. DOI: 10.1016/j.energy.201405.080 0360-5442.