1 |
Lepore, R., Renotte, C., Frere, M. and Dumont, E., Energy Consumption Reduction in Office Buildings using Model-based Predictive Control, Proceedings of the 13th IBPSA Conference, August 26-28, Chambery, France, p.p.2459-2465, 2013
|
2 |
Neal, R.M., Bayesian Learning for Neural Networks, Springer, New York, Lecture Notes in Statistics 118, 1996
|
3 |
Nouidui, T., Wetter, M. and Zuo, W., Functional Mock-up Unit for Co-simulation Import in EnergyPlus, Journal of Building Performance Simulation, 7(3), p.p.192-202, 2014
DOI
|
4 |
Park, C.S. and Augenbroe, G., Local vs. Integrated Control Strategies for Double-Skin Systems, Automation in Construction, Vol.30, p.p.50-56, 2013
DOI
ScienceOn
|
5 |
Rasmussen, C.E., Gaussian Processes in Machine Learning, Technical report, Max Planck Institute for Biological Cybernetics, 72076 Tubingen, Germany, 2004
|
6 |
Rasmussen, C.E. and Williams, C.K.I., Gaussian Processes for Machine Learning, the MIT Press, ISBN 026218253X, 2006
|
7 |
Schaffer, J.D., Multi objective optimization with vector evaluated genetic algorithms, Proceedings of the First International Conference on Genetic Algorithms, Hillsdale, New Jersey, p.p.93-100, 1985
|
8 |
Wouters, P., Heijmans, N. and Loncour, X., Outline for a General Framework for the Assessment of Innovative Ventilation Systems, RESHYVENT report, 2004
|
9 |
Suter, G., Icoglu, O., Mahdavi, A. and Spasojevic, B., Position Uncertainty in Space Scene Reconstruction for Simulation-based Lighting Control, Proceedings of the 9th IBPSA Conference, August 15-18, EcolePolytechnique de Montreal, Montreal, Canada, p.p.1191-1198, 2005
|
10 |
Vanhatalo, J., Riihimaki, J., Hartikainen, J. and Vehtari, A., Bayesian Modeling with Gaussian Processes using the MATLAB toolbox GPstuff. submitted, 2011
|
11 |
Wetter, M., Co-simulation of Building Energy and Control Systems with the Building Controls Virtual Test Bed, Journal of Building Performance Simulation, 4(3), p.p.185-203, 2011
DOI
|
12 |
Yoon, S.H., Park, C.S. and Augenbroe, G., On-line Parameter Estimation and Optimal Control Strategy of a Double-Skin System, Building and Environment, 46(5), p.p.1141-1150, 2011
DOI
ScienceOn
|
13 |
Zhang, Y., O'Neill, Z., Wanger, T. and Augenbroe, G., An Inverse Model with Uncertainty Quantification to Estimate the Energy Performance of an Office Building, Proceedings of the 13th IBPSA Conference, August 26-28, Chambery, France, p.p.614-621, 2013
|
14 |
Zhao, J., Lam, K.P. and Ydstie, B.E., Energyplus Model-based Predictive Control (EMPC) by using MATLA/SIMULINK and MLE+, Proceedings of the 13th IBPSA Conference, August 26-28, Chambery, France, p.p.2466-2473, 2013
|
15 |
윤경수, 박철수, 이중 외피 시스템의 수준별 제어, 대한건축학회논문집, 26(11), p.p.317-326, 2010
|
16 |
윤성환, 박철수, 이중외피 시스템의 정적 및 동적 제어 전략, 대한건축학회논문집, 25(2), p.p.223-231, 2009
|
17 |
김영진, 윤경수, 박철수, 패턴 서치 알고리즘과 유전자 알고리즘을 이용한 이중외피 시스템의 최적 제어, 대학건축학회논문집, 27(7), p.p.239-248, 2011
|
18 |
김영진, 박철수, 김인한, 몬테카를로 빌딩 시뮬레이션의 샘플링 방법과 모집단 추정, 대학건축학회논문집 28(6), p.p.227-238, 2012
|
19 |
Abushakra, B., An Inverse Model to Predict and Evaluate the Energy Performance of Large Commercial and Institutional Buildings, IBPSA Conference Proceedings, Prague, Czech Republic, 1997
|
20 |
윤성환, 박철수, 기존 건축물을 위한 x-Ray 개념의 에너지 모델 작성과 평가, 대한건축학회논문집, 30(1), p.p.235-244, 2014
|
21 |
Afram, A. and Janabi-Sharifi, F., Theory and Applications of HVAC Control Systems-A Review of Model Predictive Control (MPC), Building and Environment, Vol.72, p.p.343-355, 2014
DOI
ScienceOn
|
22 |
ASHRAE, Guideline14-Measurement of energy and demand savings, American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Atlanta, GA, 2002
|
23 |
Augenbroe, G., Brown, J., Heo1, Y.S., Kim, S.H., Li, Z., McManus, S. and Zhao, F., Lessons from an Advanced Building Simulation Course, The Third National Conference of IBPSA-USA, Berkeley, California, July 30-August 1, 2008
|
24 |
Bazjanac, V., BIM that Supports Life Cycle of Buildings, BuildingSMART Korea International Forum 2010, Seoul, Korea, April 21, 2010
|
25 |
de Wit, S., Uncertainty in Prediction of Thermal Comfort in Buildings, Ph.D. thesis, Tu Delft Netherlands, 2001
|
26 |
Bernal, W., Madhur, B., Truong, N. and Rahul, M., MLE+: A Tool for Integrated Design and Deployment of Energy Efficient Building Controls, 4th ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, Toronto, 2012
|
27 |
Breesch, H. and Janssens, A., Building Simulation to Predict the Performances of Natural Night Ventilation: Uncertainty and Sensitivity Analysis, Proceedings of the 9th IBPSA Conference, August 15-18, Ecole Polytechnique de Montreal, Montreal, Canada, p.p.115-122, 2005
|
28 |
Gilks, W. R., Richardson, S. and Spiegelhalter, D., Markov Chain Monte Carlo in Pratice, Chapman and Hall, 1995
|
29 |
de Wilde, P. and Tian, W., Predicting the Performance of an Office under Climate Change: A Study of Metrics, Sensitivity and Zonal Resolution, Energy and Buildings, Vol.42, p.p.1674-1684, 2010
DOI
ScienceOn
|
30 |
Dijk, H. and Spiekman, M., Energy Performance of Buildings; Outline for Harmonised EP Procedures. Final report EU SAVE ENPER project, Task B6. TNO Building and Construction Research, Delft(NL), June 29, 2004 (http://www.enper.org)
|
31 |
Heo, Y.S. and Zavala, V.M., Gaussian Process Modeling for Measurement and Verification of Building Energy Savings, Energy and Buildings, Vol.53, p.p.7-18, 2012
|
32 |
Herzog, S., Atabay, D., Jungwirth, J. and Mikulovic, V., Self-adapting Building Models for Model Predictive Control, Proceedings of the 13th IBPSA Conference, August 26-28, Chambery, France, p.p.2489-2493, 2013
|
33 |
Hopfe, C.J., Uncertainty and Sensitivity Analysis in Building Performance Simulation for Decision Support and Design Optimization. PhD thesis, Technische Universiteit Eindhoven, 2009
|
34 |
Kim, Y.J., Ahn, K.U., Park, C.S. and Kim, I.H., Gaussian Emulator for Stochastic Optimal Design of a Double Glazing System, Proceedings of the 13th IBPSA Conference, August 25-28, Chambery, France, p.p.2217-2224, 2013a
|
35 |
Hyun, S.H., Park, C.S. and Augenbroe, G., Analysis of Uncertainty in Natural Ventilation Predictions of High-rise Apartment Buildings, Building Services Engineering Research and Technology, 29(4), p.p.311-326, 2008
DOI
ScienceOn
|
36 |
ISO 13790, Energy Performance of Buildings-Calculation of Energy Use for Space Heating and Cooling, 2008
|
37 |
Kocijan, J., Murray-Smith, R., Rasmussen, C.E. and Likar, B., Predictive Control with Gaussian Process Models, Proceedings of IEEE, Region 8 Eurocon 2003: Computer as a Tool, Piscataway, NJ, USA, September, pp.352-356, 2003
|
38 |
Kim, D.W. and Park, C.S., A Heterogeneous System Simulation of a Double Skin Facade, Proceedings of the 12th IBPSA Conference, November 14-16, Sydney, Australia, p.p.601-608, 2011
|
39 |
Kim, Y.J., Yoon, S.H. and Park, C.S., Stochastic Comparison between Simplified Energy Calculation and Dynamic Simulation, Energy and Buildings, Vol.64, p.p.332-342, 2013b
DOI
|
40 |
Kim, Y.J., Ahn, K.U. and Park, C.S., Decision Making of HVAC System using Bayesian Markov Chain Monte Carlo method, Energy and Buildings, Vol.72, p.p.112-121, 2014
DOI
ScienceOn
|
41 |
Kocijan, J. and Murray-Smith, R., Nonlinear Predictive Control with a Gaussian Process Model, Switching and Learning, LNCS 3355, p.p.185-200, 2005
|
42 |
Kotek, P., Jordan, F., Kabele, K. and Hensen, J., Technique of Uncertainty and Sensitivity Analysis for Sustainable Building Energy Systems Performance Calculations, Proceedings of the 10th IBPSA Conference, September 3-6, Beijing, China, p.p.629-636, 2007
|
43 |
Monfet, D. and Zmeureanu, R., Identification of the Electric Chiller Model for the EnergyPlus Program using Monitored Data in an Existing Cooling Plant, Proceedings of the 12th IBPSA Conference, November 14-16, Sydney, Australia, p.p.530-537, 2011
|
44 |
Lee, K.P. and Cheng, T.A., A Simulation-optimization Approach for Energy Efficiency of Chilled Water System, Energy and Buildings, Vol.54, p.p.290-296, 2012
DOI
ScienceOn
|
45 |
MacDonald, I.A., Quantifying the Effects of Uncertainty in Building Simulation, Ph.D. thesis, University of Strathclyde, Scotland, 2002
|
46 |
ASHRAE, ASHRAE Fundamentals, American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Atlanta, GA, 2013
|