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  1. National Taiwan Ocean University Research Hub
  2. 海洋科學與資源學院
  3. 海洋環境資訊系
請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/10919
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dc.contributor.authorWei, Chih-Chiangen_US
dc.date.accessioned2020-11-21T06:54:21Z-
dc.date.available2020-11-21T06:54:21Z-
dc.date.issued2017-09-
dc.identifier.issn0167-6105-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/10919-
dc.description.abstractIn this study, we developed a conceptual weather environmental forecasting system (CWEFS) for predicting the failure of under-construction structures during typhoons. Major functions of the developed system include 1) forecasting hourly typhoon wind velocity, 2) analyzing structure reference load during the construction stage, 3) identifying potential failure of under-construction structures, and 4) evaluating the weather in future hours to determine whether the conditions are suitable for work. Data-driven models, namely support vector machines for regression (SVRs), regression, and two decision trees (namely C5.0 and CART) were employed in this study as forecasting techniques to predict the wind velocity on Orchid Island, Taiwan, the study site. Structure reference load analysis was performed using a finite element model to evaluate the reference load on an experimental tank under construction. Typhoons Nanmadol (2011) and Saola (2012) were selected for real-time simulation by using the proposed CWEFS. This study identified potential collapses by using 1- to 6-h-ahead wind speed predictions. However, prediction errors inevitably occur. The results showed that the SVRs provided excellent prediction accuracy compared with regression, C5.0, and CART regarding the average time error between the observed and predicted values in all structure scenarios. A high forecast time error might result in increased construction costs and delays in construction schedules. Thus, we suggest that shorter prediction windows (e.g., 1 and 2 h) and models with higher prediction accuracy (e.g., SVR and C5.0) be employed to create a reasonable warning system.en_US
dc.language.isoen_USen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.ispartofJ WIND ENG IND AERODen_US
dc.subjectDECISION TREESen_US
dc.subjectNEURAL-NETWORKSen_US
dc.subjectTIME-SERIESen_US
dc.subjectWIND-SPEEDen_US
dc.subjectMODELen_US
dc.subjectPREDICTIONen_US
dc.subjectSIMULATIONen_US
dc.subjectREGRESSIONen_US
dc.subjectREGIONSen_US
dc.subjectCOASTALen_US
dc.titleConceptual weather environmental forecasting system for identifying potential failure of under-construction structures during typhoonsen_US
dc.typejournal articleen_US
dc.identifier.doi10.1016/j.jweia.2017.05.010-
dc.identifier.isiWOS:000408299700005-
dc.identifier.url<Go to ISI>://WOS:000408299700005
dc.relation.journalvolume168en_US
dc.relation.pages48-59en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.grantfulltextnone-
item.openairetypejournal article-
crisitem.author.deptCollege of Ocean Science and Resource-
crisitem.author.deptDepartment of Marine Environmental Informatics-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.deptCenter of Excellence for Ocean Engineering-
crisitem.author.deptData Analysis and Administrative Support-
crisitem.author.orcid0000-0002-2965-7538-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Ocean Science and Resource-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCenter of Excellence for Ocean Engineering-
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