Directional search algorithm for hierarchical model development and selection. (February 2019)
- Record Type:
- Journal Article
- Title:
- Directional search algorithm for hierarchical model development and selection. (February 2019)
- Main Title:
- Directional search algorithm for hierarchical model development and selection
- Authors:
- Sun, Bo
Gardoni, Paolo - Abstract:
- Highlights: Single-level model and hierarchical model system are well defined. System model calibration approach is established based on the Bayesian rule. System model selection approach is established based on the uncertainty propagation theory. A directional search algorithm is proposed to improve the efficiency of hierarchical model selection. Proposed approaches are verified in two examples. Abstract: A comprehensive directional search algorithm is developed for the model development and selection of hierarchical models systems. A hierarchical model system is a system of nested single-level models that includes different model candidates that can be constructed and calibrated independently. Adjusted single-level model candidates for hierarchical (multi-level) model selection are constructed following the general process of probabilistic single-level model development and selection. An uncertainty propagation matrix is defined to capture the uncertainty levels for all the possible candidate model systems. The uncertainty propagation measurements in the uncertainty propagation matrix are calculated based on the uncertainty propagation theory. A directional search algorithm is proposed to improve the efficiency of finding the best hierarchical model system. The best model system has the desired balance between accuracy and conciseness. The search direction at every search step is determined based on the importance measures of the single-level models. As two examples of theHighlights: Single-level model and hierarchical model system are well defined. System model calibration approach is established based on the Bayesian rule. System model selection approach is established based on the uncertainty propagation theory. A directional search algorithm is proposed to improve the efficiency of hierarchical model selection. Proposed approaches are verified in two examples. Abstract: A comprehensive directional search algorithm is developed for the model development and selection of hierarchical models systems. A hierarchical model system is a system of nested single-level models that includes different model candidates that can be constructed and calibrated independently. Adjusted single-level model candidates for hierarchical (multi-level) model selection are constructed following the general process of probabilistic single-level model development and selection. An uncertainty propagation matrix is defined to capture the uncertainty levels for all the possible candidate model systems. The uncertainty propagation measurements in the uncertainty propagation matrix are calculated based on the uncertainty propagation theory. A directional search algorithm is proposed to improve the efficiency of finding the best hierarchical model system. The best model system has the desired balance between accuracy and conciseness. The search direction at every search step is determined based on the importance measures of the single-level models. As two examples of the proposed hierarchical model development and selection process, the best hierarchical model systems are determined for the modeling of the concrete carbonation depth and the modeling of the flutter capacity for cable-stayed bridge decks. … (more)
- Is Part Of:
- Reliability engineering & system safety. Volume 182(2019)
- Journal:
- Reliability engineering & system safety
- Issue:
- Volume 182(2019)
- Issue Display:
- Volume 182, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 182
- Issue:
- 2019
- Issue Sort Value:
- 2019-0182-2019-0000
- Page Start:
- 194
- Page End:
- 207
- Publication Date:
- 2019-02
- Subjects:
- Hierarchical model -- Model selection -- Uncertainty propagation -- Importance measure
Reliability (Engineering) -- Periodicals
System safety -- Periodicals
Industrial safety -- Periodicals
Fiabilité -- Périodiques
Sécurité des systèmes -- Périodiques
Sécurité du travail -- Périodiques
620.00452 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09518320 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.ress.2018.09.013 ↗
- Languages:
- English
- ISSNs:
- 0951-8320
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 7356.422700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14568.xml