Generalized Extreme Value-Pareto Distribution Function and Its Applications in Ocean Engineering
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摘要
In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the new model to estimate the design wave height for 500, 700 and 1000-year return periods. Results show that the design wave height from Weibull–Pareto distribution is between that of the Weibull distribution and that of the Pearson-Ⅲ distribution.For the 500-year return period design wave height, the results from the new model is 1.601% lower than those from the Weibull distribution and 1.319% higher than those from the Pearson-Ⅲ distribution. The Weibull–Pareto distribution innovatively considers the fractal features, extreme-value statistics and the truncated data in the derivation process. Therefore, it is a more holistic and practical model for estimating the design parameters in marine and coastal environments.
In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the new model to estimate the design wave height for 500, 700 and 1000-year return periods. Results show that the design wave height from Weibull–Pareto distribution is between that of the Weibull distribution and that of the Pearson-Ⅲ distribution.For the 500-year return period design wave height, the results from the new model is 1.601% lower than those from the Weibull distribution and 1.319% higher than those from the Pearson-Ⅲ distribution. The Weibull–Pareto distribution innovatively considers the fractal features, extreme-value statistics and the truncated data in the derivation process. Therefore, it is a more holistic and practical model for estimating the design parameters in marine and coastal environments.
In this paper, we establish a generalized extreme Value-Pareto distribution model and derive an analytical expression of Weibull–Pareto distribution model. Based on a data sample of 26-year wave height, we adopt the new model to estimate the design wave height for 500, 700 and 1000-year return periods. Results show that the design wave height from Weibull–Pareto distribution is between that of the Weibull distribution and that of the Pearson-Ⅲ distribution.For the 500-year return period design wave height, the results from the new model is 1.601% lower than those from the Weibull distribution and 1.319% higher than those from the Pearson-Ⅲ distribution. The Weibull–Pareto distribution innovatively considers the fractal features, extreme-value statistics and the truncated data in the derivation process. Therefore, it is a more holistic and practical model for estimating the design parameters in marine and coastal environments.
引文
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Wang,L.P.,Chen,B.Y.,Chen,C.,Chen,Z.S.and Liu,G.L.,2016.Application of linear mean-square estimation in ocean engineering,China Ocean Engineering,30(1),149-160.
Wang,L.P.,Chen,B.Y.,Zhang,J.F.and Chen,Z.S.,2013.A new model for calculating the design wave height in typhoon-affected sea areas,Natural Hazards,67(2),129-143.
Wang,L.P.,Huang,G.L.,Chen,Z.S.,Liang,B.C.and Liu,G.L.,2014.Risk analysis and assessment of overtopping concerning sea dikes in the case of storm surge,China Ocean Engineering,28(4),479-487.
Wang,L.P.,Liu,G.L.,Chen,B.Y.and Wang,L.,2015.New Method for Calculating Typhoon-Influenced Sea Area Designed Wave Height Based on Maximum Entropy Principle,CN 102063564B.(in Chinese)
Wang,L.P.,Xu,X.,Liu,G.L.,Chen,B.Y.and Chen,Z.S.,2017.Anew method to estimate wave height of specified return period,Chinese Journal of Oceanology and Limnology,35(5),1002-1009.
Xian,S.Y.,Feng,K.R.,Lin,N.,Marsooli,R.,Chavas,D.,Chen,J.and Hatzikyriakou,A.,2018.Brief communication:Rapid assessment of damaged residential buildings in the Florida Keys after Hurricane Irma,Natural Hazards and Earth System Sciences,18(7),2041-2045.
Zhang K.Y.and Kleit,A.N.,2016.Mining rate optimization considering the stockpiling:A theoretical economics and real option model,Resources Policy,47,87-94.
Zhang,K.Y.,Olawoyin,R.,Nieto A.and Kleit,A.N.,2018.Risk of commodity price production cost and time to build in resource economics,Environment,Development and Sustainability,20(6),2521-2544.
Zhang,S.F.,Shen,W.,Li,D.S.,Zhang,X.W.and Chen,B.Y.,2018.Nondestructive ultrasonic testing in rod structure with a novel numerical laplace based wavelet finite element method,Latin American Journal of Solids and Structures,15(7),1-17.
Barrs,A.and Chen,B.Y.,2018.How Emerging Technologies Could Transform Infrastructure,http://www.governing.com/govinstitute/voices/col-hyperlane-emerging-technologies-transform-infrastructure.html[2018-03-06].
Cai,W.,Chan,J.and Garmire,D.,2011.3-axes MEMS hall-effect sensor,Proceedings of 2011 IEEE Sensors Applications Symposium,IEEE,San Antonio,TX,USA,pp.141-144.
Cai,W.,Huang,L.and Wen,W.J.,2016.2.4 GHz class AB power amplifier for wireless medical sensor network,International Journal of Enhanced Research in Science,Technology&Engineering,5(4),94-98.
Chen,B.Y.and Wang,B.Y.,2017.Location selection of logistics center in e-commerce network environments,American Journal of Neural Networks and Applications,3(4),40-48.
Chen,B.Y.,Escalera,S.,Guyon,I.,Ponce-López,V.,Shah,N.and Simón,M.O.,2016.Overcoming calibration problems in pattern labeling with pairwise ratings:application to personality traits,Proceedings of Computer Vision-ECCV 2016 Workshops,Springer,Amsterdam,The Netherlands,pp.419-432.
Chen,B.Y.,Liu,G.L.and Wang,L.P.,2017a.Predicting joint return period under ocean extremes based on a maximum entropy compound distribution model,International Journal of Energy and Environmental Science,2(6),117-126.
Chen,B.Y.,Liu,G.L.,Wang,L.P.,Zhang,K.Y.and Zhang,S.F.,2018.Determination of water level design for an estuarine city,Journal of Oceanology and Limnology,37(1),20-29.
Chen,B.Y.,Yang,Z.Y.,Huang,S.Y.,Du,X.Z.,Cui,Z.W.,Bhimani,J.,Xie,X.and Mi,N.F.,2017b.Cyber-physical system enabled nearby traffic flow modelling for autonomous vehicles,Proceedings of the 2017 IEEE 36th International Performance Computing and Communications Conference,IEEE,San Diego,CA,USA.
de Haan,L.and Ferreira,A.,2006.Extreme Value Theory:An Introduction.Springer,New York.
Escalante,H.J.,Ponce-López,V.,Wan,J.,Riegler,M.A.,Chen,B.Y.,Clapés,A.,Escalera,S.,Guyon,I.,Baró,X.,Halvorsen,P.,Müller,H.and Larson,M.,2016.Chalearn joint contest on multimedia challenges beyond visual analysis:An overview,Proceedings of the2016 23rd International Conference on Pattern Recognition(ICPR),IEEE,Cancun,Mexico,pp.67-73.
Fu,H.L.and Liu,X.J.,2017.Research on the phenomenon of Chinese residents’spiritual contagion for the reuse of recycled water based on SC-IAT,Water,9(11),846.
Fu,H.L.,Li,Z.X.,Liu,Z.J.and Wang,Z.L.,2018.Research on big data digging of hot topics about recycled water use on micro-blog based on particle swarm optimization,Sustainability,10(7),2488.
Jiang,S.,Lian,M.J.,Lu,C.W.,Gu,Q.H.,Ruan,S.L.and Xie,X.C.,2018.Ensemble prediction algorithm of anomaly monitoring based on big data analysis platform of open-pit mine slope,Complexity,2018,1048756.
Liu,D.F.,Wang,L.P.and Pang,L.,2006.Theory of multivariate compound extreme value distribution and its application to extreme sea state prediction,Chinese Science Bulletin,51(23),2926-2930.
Liu,G.L.,Chen,B.Y.,Wang,L.P.,Zhang,S.F.,Zhang,K.Y.and Lei,X.,2018.Wave height statistical characteristic analysis,Journal of Oceanology and Limnology,36(4),1-13.
Liu,G.L.,Zheng,Z.J.,Wang,L.P.,Chen,B.Y.,Dong,Y.J.,Xu,P.Y.,Wang,J.and Wang,C.,2015.Power-Type Wave Absorbing Device and Using Method Thereof,CN 105113452B.(in Chinese)
Liu,X.J.,He,Y.Q.,Fu,H.L.,Chen,B.Y.,Wang,M.M.and Wang,Z.L.,2018.How environmental protection motivation influences on residents’recycled water reuse behaviors:A case study in Xi’an City,Water,10(9),1282.
Ponce-López,V.,Chen,B.Y.,liu,M.O.,Corneanu,C.,Clapés,A.,Guyon,I.,Baró,X.,Escalante,H.J.and Escalera,S.,2016.ChaLearn LaP 2016:First round challenge on first impressionsdataset and results,Proceedings of Computer Vision-ECCV 2016Workshops,Springer,Amsterdam,The Netherlands,pp.400-418.
Wang,L.P.and Wang,L.,2013.Method for Calculating Combined Return Period of Ocean Extreme Value Considering Typhoon Influence,CN 102063527B.(in Chinese)
Wang,L.P.,Chen,B.Y.,Chen,C.,Chen,Z.S.and Liu,G.L.,2016.Application of linear mean-square estimation in ocean engineering,China Ocean Engineering,30(1),149-160.
Wang,L.P.,Chen,B.Y.,Zhang,J.F.and Chen,Z.S.,2013.A new model for calculating the design wave height in typhoon-affected sea areas,Natural Hazards,67(2),129-143.
Wang,L.P.,Huang,G.L.,Chen,Z.S.,Liang,B.C.and Liu,G.L.,2014.Risk analysis and assessment of overtopping concerning sea dikes in the case of storm surge,China Ocean Engineering,28(4),479-487.
Wang,L.P.,Liu,G.L.,Chen,B.Y.and Wang,L.,2015.New Method for Calculating Typhoon-Influenced Sea Area Designed Wave Height Based on Maximum Entropy Principle,CN 102063564B.(in Chinese)
Wang,L.P.,Xu,X.,Liu,G.L.,Chen,B.Y.and Chen,Z.S.,2017.Anew method to estimate wave height of specified return period,Chinese Journal of Oceanology and Limnology,35(5),1002-1009.
Xian,S.Y.,Feng,K.R.,Lin,N.,Marsooli,R.,Chavas,D.,Chen,J.and Hatzikyriakou,A.,2018.Brief communication:Rapid assessment of damaged residential buildings in the Florida Keys after Hurricane Irma,Natural Hazards and Earth System Sciences,18(7),2041-2045.
Zhang K.Y.and Kleit,A.N.,2016.Mining rate optimization considering the stockpiling:A theoretical economics and real option model,Resources Policy,47,87-94.
Zhang,K.Y.,Olawoyin,R.,Nieto A.and Kleit,A.N.,2018.Risk of commodity price production cost and time to build in resource economics,Environment,Development and Sustainability,20(6),2521-2544.
Zhang,S.F.,Shen,W.,Li,D.S.,Zhang,X.W.and Chen,B.Y.,2018.Nondestructive ultrasonic testing in rod structure with a novel numerical laplace based wavelet finite element method,Latin American Journal of Solids and Structures,15(7),1-17.