• Title/Summary/Keyword: 연안.해양보호구역

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A Study of Outlier Detection Using the Mixture of Extreme Distributions Based on Deep-Sea Fishery Data (원양어선 조업 데이터의 혼합 극단분포를 이용한 이상점 탐색 연구)

  • Lee, Jung Jin;Kim, Jae Kyoung
    • The Korean Journal of Applied Statistics
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    • v.28 no.5
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    • pp.847-858
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    • 2015
  • Deep-sea fishery in the Antarctic Ocean has been actively progressed by the developed countries including Korea. In order to prevent the environmental destruction of the Antarctic Ocean, related countries have established the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and have monitored any illegal unreported or unregulated fishing. Fishing of tooth fish, an expensive fish, in the Antarctic Ocean has increased recently and high catches per unit effort (CPUE) of fishing boats, which is suspicious for an illegal activity, have been frequently reported. The data of CPUEs in a fishing area of the Antarctic Ocean often show an extreme Distribution or a mixture of two extreme distributions. This paper proposes an algorithm to detect an outlier of CPUEs by using the mixture of two extreme distributions. The parameters of the mixture distribution are estimated by the EM algorithm. Log likelihood value and posterior probabilities are used to detect an outlier. Experiments show that the proposed algorithm to detect outlier of the data can be adopted instead of simple criteria such as a CPUE is greater than 1.