Open Access
Issue |
Int. J. Metrol. Qual. Eng.
Volume 6, Number 3, 2015
|
|
---|---|---|
Article Number | 308 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/ijmqe/2015022 | |
Published online | 23 October 2015 |
- IEA, “Key World Energy Statistics 2014 – Key World 2014.pdf,” 2014. [Online]. Available: http://www.iea.org/publications/freepublications/publication/KeyWorld2014.pdf. [Accessed: 10-Dec-2014]. [Google Scholar]
- L. Pérez-Lombard, J. Ortiz, C. Pout, A review on buildings energy consumption information, Energy Build. 40, 394–398 (2008) [CrossRef] [Google Scholar]
- ASHRAE, ASHRAE Guideline 14, Measurement of energy and demand savings (2002) [Google Scholar]
- P. de Wilde, The gap between predicted and measured energy performance of buildings: A framework for investigation, Autom. Constr. 41, 40–49 (2014) [CrossRef] [Google Scholar]
- A.C. Menezes, A. Cripps, D. Bouchlaghem, R. Buswell, Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap, Appl. Energy 97, 355–364 (2012) [Google Scholar]
- S. De Wit, G. Augenbroe, Analysis of uncertainty in building design evaluations and its implications, Energy Build. 34, 951–958 (2002) [CrossRef] [Google Scholar]
- S. Attia, M. Hamdy, W. O’Brien, S. Carlucci, Assessing gaps and needs for integrating building performance optimization tools in net zero energy buildings design, Energy Build. 60, 110–124 (2013) [CrossRef] [Google Scholar]
- GUM, Guide to the Expression of Uncertainty in Measurement (1995) [Google Scholar]
- O. Bodnar, G. Wübbeler, C. Elster, On the application of Supplement 1 to the GUM to non-linear problems, Metrologia 48, 333 (2011) [CrossRef] [Google Scholar]
- K. Weise, W. Woger, A Bayesian theory of measurement uncertainty, Meas. Sci. Technol. 4, 1 (1993) [CrossRef] [Google Scholar]
- I. Lira, G. Kyriazis, Bayesian inference from measurement information, Metrologia 36, 163 (1999) [CrossRef] [Google Scholar]
- A. Caucheteux, A Building Energy Efficiency Characterisation Method (BEECHAM) to Assess Existing Buildings Performance (2012) [Google Scholar]
- C. Elster, W. Wöger, M.G. Cox, Draft GUM Supplement 1 and bayesian analysis, Metrologia 44, L31 (2007) [CrossRef] [Google Scholar]
- M. Ángeles Herrador, A.G. González, Evaluation of measurement uncertainty in analytical assays by means of Monte-Carlo simulation, Talanta 64, 415–422 (2004) [CrossRef] [PubMed] [Google Scholar]
- M.G. Cox, B.R. Siebert, The use of a Monte Carlo method for evaluating uncertainty and expanded uncertainty, Metrologia 43, S178 (2006) [CrossRef] [Google Scholar]
- C. Elster, B. Toman, Bayesian uncertainty analysis under prior ignorance of the measurand versus analysis using the Supplement 1 to the Guide: a comparison, Metrologia 46, 261 (2009) [CrossRef] [Google Scholar]
- I. Lira, D. Grientschnig, Bayesian assessment of uncertainty in metrology: a tutorial, Metrologia 47, R1 (2010) [CrossRef] [Google Scholar]
- I. Lira, W. Wöger, Bayesian evaluation of the standard uncertainty and coverage probability in a simple measurement model, Meas. Sci. Technol. 12, 1172 (2001) [CrossRef] [Google Scholar]
- R. Kacker, A. Jones, On use of Bayesian statistics to make the Guide to the Expression of Uncertainty in Measurement consistent, Metrologia 40, 235 (2003) [CrossRef] [Google Scholar]
- S.A. Kalogirou, C.C. Neocleous, C.N. Schizas, Building heating load estimation using artificial neural networks, in Proceedings of the 17th international conference on Parallel architectures and compilation techniques, (1997), Vol. 8, p. 14 [Google Scholar]
- T. Olofsson, S. Andersson, Long-term energy demand predictions based on short-term measured data, Energy Build. 33, 85–91 (2001) [CrossRef] [Google Scholar]
- Q. Li, Q. Meng, J. Cai, H. Yoshino, A. Mochida, Applying support vector machine to predict hourly cooling load in the building, Appl. Energy 86, 2249–2256 (2009) [CrossRef] [Google Scholar]
- D. Coakley, P. Raftery, M. Keane, A review of methods to match building energy simulation models to measured data, Renew. Sustain. Energy Rev. 37, 123–141 (2014) [Google Scholar]
- AFNOR, Norme Européenne, Norme Française, Performance Energetique des batiments, Calcul des besoins d’énergie pour le chauffage, Batiments résidentiels. Norme AFNOR, Aout-1999. [Google Scholar]
- A. Trnsys, Transient System Simulation Program, University. Wis. (2000) [Google Scholar]
- C. Elster, B. Toman, Bayesian uncertainty analysis for a regression model versus application of GUM Supplement 1 to the least-squares estimate, Metrologia 48, 233 (2011) [CrossRef] [Google Scholar]
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