A new zone temperature predictive modeling for energy saving in buildings

Procedia Engineering

Volumn 49, Issue , 2012, Pages 142-151

  Huang, Hao ^a   Chen, Lei ^a   Mohammadzaheri, Morteza ^a   Hu, Eric ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

Artificial neural networks (ANN); HVAC; Multi zone

Indexed keywords

EID: 84882290433     PISSN: 18777058     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.proeng.2012.10.122     Document Type: Conference Paper

References (14)

1. Wang, S. and Ma, Z. Supervisory and Optimal Control of Building HVAC Systems: A Review. HVAC&R Research, 14, 1 (2008/01/01 2008), 3-32.
2. Xinhua, X., Shengwei, W. and Gongsheng, H. Robust MPC for temperature control of air-conditioning systems concerning on constraints and multitype uncertainties. Building Services Engineering Research & Technology; 2010, 39-55.
3. Ruano, A. E., Crispim, E. M., Conceição, E. Z. E. and Lúcio, M. M. J. R. Prediction of building's temperature using neural networks models. Energy and Buildings; 2006, 682-694.
4. Patil, S. L., Tantau, H. J. and Salokhe, V. M. Modelling of tropical greenhouse temperature by auto regressive and neural network models. Biosystems Engineering; 2008, 423-431.
5. Mustafaraj, G., Lowry, G. and Chen, J. Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural network models for an open office. Energy and Buildings; 2011, 1452-1460.
6. Mechaqrane, A. and Zouak, M. A comparison of linear and neural network ARX models applied to a prediction of the indoor temperature of a building. Neural Computing & Applications; 2004, 32-37.
7. Lu, T. and Viljanen, M. Prediction of indoor temperature and relative humidity using neural network models: model comparison. Neural Computing & Applications; 2009, 345-357.
8. Yang, I.-H., Yeo, M.-S. and Kim, K.-W. Application of artificial neural network to predict the optimal start time for heating system in building. Energy Conversion and Management; 2003, 2791-2809.
9. Yang, I.-H. and Kim, K.-W. Prediction of the time of room air temperature descending for heating systems in buildings. Building and Environment; 2004, 19-29.
10. Moon, J. W. and Kim, J.-J. ANN-based thermal control models for residential buildings. Building and Environment; 2010, 1612-1625.
11. May,R., Dandy,G., Maier, H. "Review of input variable selection methods for Artificial Neural Networks Artificial Neural Networks - In Suzuki, K, Methodological Advances and Biomedical Applications; 2011, 19-42.
12. Mirsephai, A., Mohammadzaheri, M., Chen, L. and O'Neill, B. An artificial intelligence approach to inverse heat transfer modeling of an irradiative dryer. International Communications in Heat and Mass Transfer; 2012, 40-45.
13. Mohammadzaheri, M. and Chen, L. Double-command fuzzy control of a nonlinear CSTR. Korean Journal of Chemical Engineering; 2010, 19-31.
14. Mark H.B, Martin T.H, Hagan, Howard B D .Neural network toolbox user's guide. R2011b