Editorial Statistical and Probabilistic Approach in...
3
Editorial Statistical and Probabilistic Approach in Monitoring-Based Structure Rating and Risk Assessment Ting-Hua Yi, 1 Ying Lei, 2 Hua-Peng Chen, 3 Siamak Talatahari, 4 and Fei Kang 5 1 School of Civil Engineering, Dalian University of Technology, Dalian 116023, China 2 School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China 3 Medway School of Engineering, e University of Greenwich, Kent ME4 4TB, UK 4 Marand Faculty of Engineering, University of Tabriz, Tabriz 51368, Iran 5 School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA Correspondence should be addressed to Ting-Hua Yi; [email protected] Received 26 June 2014; Accepted 26 June 2014; Published 14 July 2014 Copyright © 2014 Ting-Hua Yi et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aging civil infrastructural facilities like long-span bridges, super-tall buildings, and large-scale space structures that form the life of a country’s economy are facing a severe crisis in some countries. Long service lives, inadequate designs, and increasing extreme loads are responsible for the current state of affairs. us, knowledge about the in-service condition of the structures is one of the most essential parts required for the engineering community. is opens a wide field for structural health monitoring (SHM) systems which are set up to assure the safe operation of structures requiring linking sensors with computational tools able to interpret sensor data in terms of structural performance [1]. Although intensive development continues on innovative sensor systems, there is still considerable uncertainty in deciding structural behavior since there are many factors in abundant measured data from the SHM system that may influence the health assessment of a structure. e most appropriate and efficient way to alleviate this multiple input problem is by the statistical and probabilistic approach including data normalization, feature extraction, statistical modeling, and risk management [2–4]. erefore, in the light of these considerations, this special issue was launched. Numerous investigators worldwide were invited to contribute their original papers and review articles on the theme of this special issue. A total of 27 technical papers are included in this special issue. ese papers present the most recent advances, progress, and ideas in the field of the statistical and probabilistic approach and its application in structure rating and risk assessment includes data com- pression and cleaning, data mining and fusing technology, pattern recognition and feature extraction, damage detection and condition assessment, and performance prediction and risk management. All of the accepted papers were carefully reviewed and found appropriate for the journal. Without a doubt, the papers reflect the state-of-the-art researches and developments of this subject. Acknowledgments As the guest editors of the special issue, we would like to express our sincere appreciation to all the authors who con- tributed their work to this exciting special issue. e guest editors also thank the reviewers for their valuable and insightful comments that greatly benefited the improvement of paper quality. is meaningful work was jointly supported by the National Natural Science Foundation of China (Grant nos. 51222806, 51121005, and 51327003) and the Specialized Research Fund for the Doctoral Program of Higher Educa- tion (Grant no. 20130041110031). Ting-Hua Yi Ying Lei Hua-Peng Chen Siamak Talatahari Fei Kang Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2014, Article ID 761341, 2 pages http://dx.doi.org/10.1155/2014/761341
Transcript of Editorial Statistical and Probabilistic Approach in...
EditorialStatistical and Probabilistic Approach in Monitoring-BasedStructure Rating and Risk Assessment
Ting-Hua Yi,1 Ying Lei,2 Hua-Peng Chen,3 Siamak Talatahari,4 and Fei Kang5
1 School of Civil Engineering, Dalian University of Technology, Dalian 116023, China2 School of Architecture and Civil Engineering, Xiamen University, Xiamen 361005, China3Medway School of Engineering, The University of Greenwich, Kent ME4 4TB, UK4Marand Faculty of Engineering, University of Tabriz, Tabriz 51368, Iran5 School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
Correspondence should be addressed to Ting-Hua Yi; [email protected]
Received 26 June 2014; Accepted 26 June 2014; Published 14 July 2014
Copyright © 2014 Ting-Hua Yi et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Aging civil infrastructural facilities like long-span bridges,super-tall buildings, and large-scale space structures thatform the life of a country’s economy are facing a severe crisisin some countries. Long service lives, inadequate designs, andincreasing extreme loads are responsible for the current stateof affairs. Thus, knowledge about the in-service conditionof the structures is one of the most essential parts requiredfor the engineering community. This opens a wide field forstructural health monitoring (SHM) systems which are setup to assure the safe operation of structures requiring linkingsensors with computational tools able to interpret sensor datain terms of structural performance [1]. Although intensivedevelopment continues on innovative sensor systems, there isstill considerable uncertainty in deciding structural behaviorsince there are many factors in abundant measured data fromthe SHM system that may influence the health assessmentof a structure. The most appropriate and efficient way toalleviate this multiple input problem is by the statistical andprobabilistic approach including data normalization, featureextraction, statistical modeling, and risk management [2–4].
Therefore, in the light of these considerations, this specialissue was launched. Numerous investigators worldwide wereinvited to contribute their original papers and review articleson the theme of this special issue. A total of 27 technicalpapers are included in this special issue.These papers presentthe most recent advances, progress, and ideas in the field ofthe statistical and probabilistic approach and its application
in structure rating and risk assessment includes data com-pression and cleaning, data mining and fusing technology,pattern recognition and feature extraction, damage detectionand condition assessment, and performance prediction andrisk management. All of the accepted papers were carefullyreviewed and found appropriate for the journal.
Without a doubt, the papers reflect the state-of-the-artresearches and developments of this subject.
Acknowledgments
As the guest editors of the special issue, we would like toexpress our sincere appreciation to all the authors who con-tributed their work to this exciting special issue. The guesteditors also thank the reviewers for their valuable andinsightful comments that greatly benefited the improvementof paper quality.This meaningful work was jointly supportedby the National Natural Science Foundation of China (Grantnos. 51222806, 51121005, and 51327003) and the SpecializedResearch Fund for the Doctoral Program of Higher Educa-tion (Grant no. 20130041110031).
Ting-Hua YiYing Lei
Hua-Peng ChenSiamak Talatahari
Fei Kang
Hindawi Publishing CorporationMathematical Problems in EngineeringVolume 2014, Article ID 761341, 2 pageshttp://dx.doi.org/10.1155/2014/761341
2 Mathematical Problems in Engineering
References
[1] T.-H. Yi, H.-N. Li, andM.Gu, “Recent research and applicationsof GPS-based monitoring technology for high-rise structures,”Structural Control andHealthMonitoring, vol. 20, no. 5, pp. 649–670, 2013.
[2] T. Yi, H. Li, and M. Gu, “Characterization and extraction ofglobal positioning system multipath signals using an improvedparticle-filtering algorithm,”Measurement Science and Technol-ogy, vol. 22, no. 7, Article ID 075101, pp. 1–11, 2011.
[3] T. H. Yi, H. N. Li, and M. Gu, “Experimental assessment ofhigh-rate GPS receivers for deformation monitoring of bridge,”Measurement, vol. 46, no. 1, pp. 420–432, 2013.
[4] T.-H. Yi, H.-N. Li, and H. M. Sun, “Multi-stage structuraldamage diagnosis method based on “energy-damage” theory,”Smart Structures and Systems, an International Journal, vol. 12,no. 3-4, pp. 345–361, 2013.
Submit your manuscripts athttp://www.hindawi.com
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
MathematicsJournal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Mathematical Problems in Engineering
Hindawi Publishing Corporationhttp://www.hindawi.com
Differential EquationsInternational Journal of
Volume 2014
Applied MathematicsJournal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Probability and StatisticsHindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Journal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Mathematical PhysicsAdvances in
Complex AnalysisJournal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
OptimizationJournal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
CombinatoricsHindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
International Journal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Operations ResearchAdvances in
Journal of
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Function Spaces
Abstract and Applied AnalysisHindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
International Journal of Mathematics and Mathematical Sciences
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
The Scientific World JournalHindawi Publishing Corporation http://www.hindawi.com Volume 2014
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Algebra
Discrete Dynamics in Nature and Society
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Decision SciencesAdvances in
Discrete MathematicsJournal of
Hindawi Publishing Corporationhttp://www.hindawi.com
Volume 2014 Hindawi Publishing Corporationhttp://www.hindawi.com Volume 2014
Stochastic AnalysisInternational Journal of
![Probabilistic Inference by Hashing and Optimization€¦ · bridging statistical physics and computer science [CP -10, IJCAI 11, NIPS 12] ... Statistical Modeling and Probabilistic](https://static.fdocuments.in/doc/165x107/5f642510c4f9567d8970916a/probabilistic-inference-by-hashing-and-optimization-bridging-statistical-physics.jpg)
![Tutorial for Metrologists on the probabilistic and statistical apparatus underlying ... · · 2017-04-28on the probabilistic and statistical apparatus ... [Glymour, 1980] does not](https://static.fdocuments.in/doc/165x107/5ad3f6027f8b9a571e8ba269/tutorial-for-metrologists-on-the-probabilistic-and-statistical-apparatus-underlying.jpg)
