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Challenging Issues in Stochastic Calibration based on Bayesian Paradigm for Building Energy Model
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- 발행기관
- 보안공학연구지원센터(IJSH) 바로가기
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- 간행물
- International Journal of Smart Home 바로가기
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- 통권
- Vol.9 No.5 (2015.05)바로가기
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- 페이지
- pp.127-142
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A246129
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Bayesian calibration has been used to transform the prior distributions of unknown inputs inherited in a building energy simulation model into the trustworthy posterior distributions. It obtains the posterior distributions using a joint distribution composed of a likelihood function and prior distributions of unknown inputs in the Bayesian paradigm. In other words, it provides higher benefits in terms of a stochastic approach than the deterministic calibration and the feasibility of their calibrated results was sufficiently discussed. However, challenging issues in Bayesian calibration still remains as follows: (1) inappropriate selection of prior distributions, (2) truncated sample dataset of the likelihood functions. The aforementioned issues can increase the risks of Bayesian calibration. This paper aims to inform the risks of Bayesian calibration associated with the aforementioned issues through a reference case study. For this study, the Gaussian Process (GP) emulator, which can be regarded as a meta-model of Building Performance Simulation (BPS) tools, was used to reduce the simulation run-time. Bayesian calibration using the GP emulator was implemented with what-if scenarios considering the aforementioned issues. And then the validated models were used for a stochastic retrofit analysis of glazing systems. With the results of the estimated posterior distributions, validation, and stochastic retrofit, this paper presents Bayesian calibration issues regarding the selection of prior distributions and sample dataset of the likelihood functions.
목차
Abstract
1. Introduction
2. Bayesian Calibration and Meta-Model
2.1. Bayesian Calibration
2.2. Gaussian Process Emulator
3. Target Building and Development & Validation of the GP Emulator
3.1. Target Building and What-if Scenarios
3.2. Development and Validation of the GP Emulator
4. Calibration Results
4.1. Priors vs. Posteriors
4.2. Model Validation
5. Case Study
6. Conclusions
Acknowledgements
References
키워드
Bayesian calibration Gaussian Process Emulator What-if scenario Building energy model저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJSH) [Science & Engineering Research Support Center, Republic of Korea(IJSH)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Smart Home
- 간기
- 격월간
- pISSN
- 1975-4094
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
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