釜山港防波堤附近交通最优分布估算研究

Woo-Ju Son, Hyeong-Tak Lee, Ik-Soon Cho
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引用次数: 3

摘要

针对自主船舶相关的其他船舶和自有船舶的导航算法和场景进行了大量的研究。然而,对于海洋构筑物通过时安全范围的选择研究较少。在本研究中,对2020年6月釜山港的海上交通进行了分析。通过Cullen和Frey图分析最优分布群,选择为伽马分布、对数正态分布和正态分布。采用Kolmogorov-Smirnov检验、Anderson-Darling检验、Cramer-von Mises检验、Akaike信息标准、Bayesian信息标准对拟合优度检验进行排序分析。分析结果表明,到达时的对数正态分布和离开时的伽马分布最适合。本研究通过蒙特卡罗模拟对32个分布进行观察,得出基于贝叶斯信息准则的最优分布,结果相同。一般情况下,在通过路线和TSS时,我们假设分布为正态分布进行研究。然而,由于不同的特征和环境,流量分布是不同的,因此期望通过本研究可以得出更准确的流量分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study on the Estimation of Optimal Traffic Distribution near Breakwater in Busan Port
ABSTRACT Many studies have been carried out regarding the navigation algorithms and scenarios of other and own ship related to autonomous ships. However, there was a lack of research on the selection of safety ranges during passing marine structures. In this study, marine traffic analysis was performed at Busan Port in June 2020. As a result of analyzing optimal distribution group through Cullen and Frey graph, it was selected as gamma distribution, lognormal distribution, and normal distribution. The statistic was analyzed by the ranking of the goodness-of-fit test according to Kolmogorov-Smirnov test, Anderson-Darling test, Cramer-von Mises test, Akaike’s Information Criterion, Bayesian Information Criterion. As a result, it was analyzed that lognormal distribution at arrival and gamma distribution at departure was best fitted. In this study, the optimal distribution was derived based on Bayesian Information Criterion through observations of 32 distributions through Monte Carlo simulation, and the results were the same. In general, when passing through the route and TSS, we performed the study by assuming the distribution as normal distribution. However, it is expected that more accurate traffic distribution can be derived based on this study, since distribution is different depending on the characteristics and circumstances.
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CiteScore
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