Statistical analysis of neural networks as applied to building energy prediction

Journal of Solar Energy Engineering, Transactions of the ASME

Volumn 126, Issue 1, 2004, Pages 592-600

  Dodier, Robert H ^a   Henze, Gregor P ^b  

^a Peter Kiewit Institute ^*  (United States)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ACQUISITION; FUNCTIONS; MATHEMATICAL MODELS; MONTE CARLO METHODS; REGRESSION ANALYSIS; STATISTICAL METHODS;

CHILLED WATER ENERGY (CHW); HOT WATER ENERGY (HW); LIGHTS AND EQUIPMENT ELECTRICITY (LTEQ); MEAN BIAS ERROR (MBE);

NEURAL NETWORKS;

EID: 8744220352     PISSN: 01996231     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.1637640     Document Type: Article

References (14)

1. Haberl, J., and Thamilseran, S., 1996, "Predicting Hourly Building Energy Use: The Great Energy Predictor Shootout II: Measuring Retrofit Savings," ASHRAE Trans., 102, Part 2.
2. MacKay, D., 1994, "Bayesian Nonlinear Modeling for the Prediction Competition," ASHRAE Trans;, 100(2), pp. 1053-1062.
3. Ohlsson, M., Peterson, C., Pi, H., Rognvaldsson, T., and Soderberg, B., 1994, "Predicting System Loads with Artificial Neural Networks," ASHRAE Trans., 100(2), pp. 1063-1074.
4. Feuston, B., and Thurtell, J., 1994, "Generalized Nonlinear Regression with Ensemble of Neural Nets," ASHRAE Trans., 100(2), pp. 1075-1080.
5. Cybenko, G., 1989, "Approximation by Superpositions of a Sigmoidal Function," Math. Control, Signals, Syst., 2, 303-314.
6. Hornik, K., Stinchcombe, M., and White, H., 1989, "Multilayer Feedforward Networks are Universal Approximates," Neural Networks, 2, pp. 359-366.
7. Dodier, R., 1995, "Statistical Properties of Neural Networks, with Application to Building Energy Prediction," Master's thesis. U. Colorado, Boulder, Colorado.
8. Kreider, J., Claridge, D., Curtiss, P., Dodier, R., Haberl, J., and Krarti, M., 1995, "Building Energy Use Prediction and System Identification using Recurrent Neural Networks," J. Sol. Energy Eng., 117(3), pp. 161-166.
9. Seher, G. A. F., and Wild, C. J. 1989, Nonlinear Regression, John Wiley and Sons, New York.
10. Raftery, A., 1994, Bayesian Model Selection in Social Research, in Sociological Methodology 1995, edited by P. Marsden, Cambridge, Mass., Blackwells.
11. Katipamula, S., 1996, "The Great Energy Predictor Shootout II: Modeling Energy Use in Large Commercial Buildings," ASHRAE Trans., 100(2).
12. Abarbanel, H. D. I., Brown, R., Sidorowich, J., and Tsimring, L. S., 1993, "Analysis of Observed Chaotic Data in Physical Systems," Rev. Mod. Phys., 65(4), pp. 1331-1392.
13. Press, W., Flannery, B., Teukolsky, S., and Vetterling, W., 1988, Numerical Recipes in C, Cambridge, Cambridge University Press.
14. Raftery, A., Madigan, D., and Hoeting, J. A., 1997, "Bayesian Model Averaging for Linear Regression Models," J American Statistical Assoc, 437, pp. 179-191.