지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Structural Engineering and Mechanics, An Int'l Journal Structural Engineering and Mechanics, An Int'l Journal Vol.74 No.1
- 발행연도
- 2020.1
- 수록면
- 55 - 67 (13page)
이용수
초록· 키워드
오류제보하기
The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.
목차
등록된 정보가 없습니다.
참고문헌 (31)
참고문헌 신청
Akaike, H. / 1998 / "Information theory and an extension of the maximum likelihood principle", Selected Papers of Hirotugu akaike, Springer / New York 19:9~213
Cheong Peng Au-Yong / 2017 / Optimal inspection frequency to mitigate the risk of building system failure / Structural Engineering and Mechanics, An Int＇l Journal 64(3):347~352
Bermudez, P. de Zea / 2010 / Parameter estimation of the generalized Pareto distribution—Part I / J. Statistical Plan. Inference 140(6):1353~1373
Caprani, C. C. / 2012 / Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification / J. Bridge Eng 18(9):901~909
Caprani, C. C. / 2008 / Characteristic traffic load effects from a mixture of loading events on short to medium span bridges / Structural Safety 30(5):394~404
Cheong Peng Au-Yong / 2017 / Optimal inspection frequency to mitigate the risk of building system failure / Structural Engineering and Mechanics, An Int＇l Journal 64(3):347~352
Bermudez, P. de Zea / 2010 / Parameter estimation of the generalized Pareto distribution—Part I / J. Statistical Plan. Inference 140(6):1353~1373
Caprani, C. C. / 2012 / Lifetime highway bridge traffic load effect from a combination of traffic states allowing for dynamic amplification / J. Bridge Eng 18(9):901~909
Caprani, C. C. / 2008 / Characteristic traffic load effects from a mixture of loading events on short to medium span bridges / Structural Safety 30(5):394~404
함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
An alternative approach to extreme value analysis for design purposes
한국수자원학회 학술발표회
2016 .01
-
Extrapolation of extreme traffic load effects on bridges based on long-term SHM data
Smart structures and systems
2016 .01
-
클러스터링 기법을 이용한 수용가별 전력 데이터 패턴 분석
KEPCO Journal on electric power and energy
2016 .01
-
합성곱 오토인코더 기반의 응집형 계층적 군집 분석
멀티미디어학회논문지
2020 .01
-
Anomaly Detection Based on Error Distribution and Clustering
한국정보과학회 학술발표논문집
2019 .06
-
Detection of Abrupt Changes in Precipitation Extremes over South Korea Using a Bayesian Approach
대한토목학회 학술대회
2016 .10
-
Extreme Value Analysis of Statistically Independent Stochastic Variables
한국해양공학회지
2019 .06
-
Utilizing Energy Storage System to Balance Three-Phase Unbalanced Distribution System Considering Peak and Low Consumption Period
대한전기학회 학술대회 논문집
2021 .07
-
군집화를 통한 딥러닝 기반 배전계통 전력조류계산
전기학회논문지
2023 .10
-
Frequency analysis of nonidentically distributed large-scale hydrometeorological extremes for South Korea
한국수자원학회 학술발표회
2015 .01
-
과학기술 논문의 참고문헌 텍스트 정보를 활용한 기술의 군집화
산업경영시스템학회지
2020 .01
-
Design of the Reconfigurable Load Distribution Control Allocator
International Journal of Aerospace System Engineering
2017 .06
-
이상치를 고려한 딥러닝 기반 웨이퍼 맵 결함 패턴 클러스터링
신뢰성응용연구
2022 .12
-
Risk Analysis of Typhoon Disaster in Korea using Extreme Value Distribution
대한산업공학회 추계학술대회 논문집
2015 .11
-
Spectral clustering based on the local similarity measure of shared neighbors
[ETRI] ETRI Journal
2022 .10
-
Fine-Grained Mobile Application Clustering Model Using Retrofitted Document Embedding
[ETRI] ETRI Journal
2017 .08
-
Synthesis of clustering algorithms based on selection of centroids
제어로봇시스템학회 국제학술대회 논문집
2018 .10
-
Experiment Results of Data-Driven Contact Clustering
대한기계학회 춘추학술대회
2019 .05
-
Gradient Boosting Machine과 Laplace Distribution 기반의 확률적 전력수요 예측 알고리즘 연구
전기학회논문지
2021 .11
-
Voltage Measurement Accuracy Assessment System for Distribution Equipment of Smart Distribution Network
Journal of Electrical Engineering & Technology
2015 .05
이 논문의 저자 정보
최근 본 자료
댓글(0)
0