신경망을 활용한 방파제 파괴확률

DC Field Value Language
dc.contributor.author 김동현 -
dc.contributor.author 박우선 -
dc.date.accessioned 2020-07-17T11:31:33Z -
dc.date.available 2020-07-17T11:31:33Z -
dc.date.created 2020-02-11 -
dc.date.issued 2004-02-29 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/31983 -
dc.description.abstract Some neural network stability models for rubble mound breakwaters are proposed and analyzed. The proposed models give the more reliable results than the well known van der Meer’s formula. Among them, the neural network model having the slope angle and the wave steepness as independent inputs shows the best performance. But the neural network model having independent input parameter for significant wave height, significant period is found not to be useful for the design of rubble mound breakwater because the design parameters exceed the training data ranges. In addition, a reliability analysis technique using the trained neural network model is proposed. Based on two analysis examples, it was found that van der Meer’s formula gives the larger or smaller failure probabilities than the neural network models. Therefore, one should be very careful in making a decision whether the designed armor units are safe or not if he/she uses only empirical formula. To avoid this situation, it is heavily recommended that more advanced models such as the neural network model proposed here should be simultaneously considered. -
dc.description.uri 1 -
dc.language English -
dc.publisher APAC Technical Committee -
dc.relation.isPartOf APAC2003 -
dc.title 신경망을 활용한 방파제 파괴확률 -
dc.title.alternative Failure Probability of Breakwater based on Neural Network -
dc.type Conference -
dc.citation.conferencePlace JA -
dc.citation.endPage 1 -
dc.citation.startPage 1 -
dc.citation.title APAC2003 -
dc.contributor.alternativeName 김동현 -
dc.contributor.alternativeName 박우선 -
dc.identifier.bibliographicCitation APAC2003, pp.1 -
dc.description.journalClass 1 -
Appears in Collections:
Marine Industry Research Division > Ocean Space Development & Energy Research Department > 2. Conference Papers
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