Probability distribution for size and mass of a nodule in the KR5 area for the development of a manganese nodule miner SCIE SCOPUS

DC Field Value Language
dc.contributor.author Kim, Saekyeol -
dc.contributor.author Cho, Su-gil -
dc.contributor.author Lim, Woochul -
dc.contributor.author Lee, Tae Hee -
dc.contributor.author Park, Sanghyun -
dc.contributor.author Hong, Sup -
dc.contributor.author Kim, Hyung-Woo -
dc.contributor.author Min, Cheon-Hong -
dc.contributor.author Choi, Jong-Su -
dc.contributor.author Ko, Young-Tak -
dc.contributor.author Chi, Sang-Bum -
dc.date.accessioned 2020-04-16T08:25:04Z -
dc.date.available 2020-04-16T08:25:04Z -
dc.date.created 2020-02-04 -
dc.date.issued 2019-01 -
dc.identifier.issn 0029-8018 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/699 -
dc.description.abstract In this paper, probability distribution for the size and mass of seafloor manganese nodules is investigated to improve the reliability of a pick-up device in a deep-sea manganese nodule miner. Because the size and mass of the manganese nodules are strongly correlated, statistical models for the size and mass cannot be estimated independently. In order to consider the correlation between the size and mass in a statistical model, the joint probability density function (PDF) is estimated by using copula. This method requires the estimation of the marginal distributions and copula for the two correlated environmental variables. However, this is significantly difficult when there is no prior knowledge of the two physical properties. The proposed method, which employs the Akaike information criterion to select the fittest marginal distributions and copula, provides a systematic procedure to determine a statistical model of correlated environmental variables without any prior knowledge of their distributions. To demonstrate the effectiveness of the proposed method, the joint PDF for the size and mass of manganese nodules is modeled by using the multivariate normal distribution and the proposed method. It was found that the proposed method provides more accurate and reliable estimation results for the two correlated environmental variables. -
dc.description.uri 1 -
dc.language English -
dc.publisher PERGAMON-ELSEVIER SCIENCE LTD -
dc.title Probability distribution for size and mass of a nodule in the KR5 area for the development of a manganese nodule miner -
dc.type Article -
dc.citation.endPage 138 -
dc.citation.startPage 131 -
dc.citation.title OCEAN ENGINEERING -
dc.citation.volume 171 -
dc.contributor.alternativeName 고영탁 -
dc.contributor.alternativeName 지상범 -
dc.identifier.bibliographicCitation OCEAN ENGINEERING, v.171, pp.131 - 138 -
dc.identifier.doi 10.1016/j.oceaneng.2018.10.041 -
dc.identifier.scopusid 2-s2.0-85057145277 -
dc.identifier.wosid 000459235600012 -
dc.type.docType Article -
dc.description.journalClass 1 -
dc.description.isOpenAccess N -
dc.subject.keywordPlus SIGNIFICANT WAVE HEIGHT -
dc.subject.keywordPlus BIVARIATE DISTRIBUTIONS -
dc.subject.keywordPlus DESIGN OPTIMIZATION -
dc.subject.keywordPlus WIND -
dc.subject.keywordPlus SEDIMENT -
dc.subject.keywordAuthor Joint probability density function -
dc.subject.keywordAuthor Seafloor manganese nodules -
dc.subject.keywordAuthor Clarion-Clipperton fracture zone -
dc.subject.keywordAuthor Copula -
dc.subject.keywordAuthor Deep-sea manganese nodule miner -
dc.subject.keywordAuthor Akaike information criterion -
dc.relation.journalWebOfScienceCategory Engineering, Marine -
dc.relation.journalWebOfScienceCategory Engineering, Civil -
dc.relation.journalWebOfScienceCategory Engineering, Ocean -
dc.relation.journalWebOfScienceCategory Oceanography -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Engineering -
dc.relation.journalResearchArea Oceanography -
Appears in Collections:
Marine Resources & Environment Research Division > Ocean Georesources Research Department > 1. Journal Articles
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