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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/37543

Title: 台灣國際商港海事事故分級之研究
Authors: 劉中平;梁金樹;朱經武
Contributors: 國立台灣海洋大學:航運管理學系
Keywords: 海事事故、灰聚類方法、事故分級、Marine accident、Gray c1ustering method、Accident c1assification
Date: 2004-12
Issue Date: 2016-03-18T08:28:29Z
Abstract: 中文摘要:台灣像一高度仰賴海洋運輸經濟的海島型國家,海事事故的預防與排除著實是維繫此一經濟體系有效運作的一項重要課題。「海事事故」為不可預期的風險,為防止或降低船拍發生海事事故,有效地提供航海人員有關各灣靠港的海事事故資料庫,以供船身自航行之參考,則顯得極為重要。而在高品質海事事故資料庫之建立上,海事事故等級劃分原則之制定,則扮演著極為重要的角色。本研究透過與各航港機關、海事評議專家及海難救護機構組織之訪談與問卷調查,及蒐集國際施行海事事故分級現況,來找尋適合建立台灣國際商港海事事故等級劃分的指標。由於我國海事報告資料所能提供分類的信息具不完全及少量的特性,且灰眾類方法於近年來應用在處理訊息不完全與不確定時,都能獲得不錯的結果,故本研究以灰眾類方法作為探討台灣國際商港事故分紋的主要工具。本研究藉由所蒐集107筆海事事故資料,以灰眾類將其分為「特殊重大事故」、「重大事故」、「一般事故」、「小事故」等四級之後,發現與人員疏失有闊的海事事故比例高達93.5%其中駕駛部的甲級船員占85.1%並發現如長的過失最為嚴重,其次為大副、輪機長及領j巷。本文之研究結果除了對航海人員可增強其對造成各類事故成因之重視與戒心,以及對遇險防護與應變技能之提升提供相當大的助益外,深信本文之海事事故分級對於海事事故之審理機構、救護機構及相關單位於審理、搜索與救護期間上,有助於妥善規劃其應投入的資源。
Abstract:Taiwan is an island country, thus the economy is highly dependent on marine transportation. Avoiding the occurrence of marine accident is an important issue for economic growth. ''Marine accident' represents risks which cannot be prevented in advance. In order to reduce marine accidents, we need to provide a quality database of marine accident in each harbor for reference. Establishing the principles to classifý marine accidents plays an important role belore constructing the quality database of marine accidents. During the process of research, we have discussed with the managers of harbor bureaus, experts of maritime arbitration, and the managers of salvage organizations, and have surveyed present marine accident classifìcation in the world in order to construct appropriate indices lor classification. Due to the incomplete inlormation of marine affairs in Taiwan for classification and inviewing that the Gray Clustering Method is an idea1 way for dealing with incomplete inlormation and uncertain causality as well as providing good results; we adopted the Method for accident classifìcαtion. After analyzing data of 107 marine accidents, we classified the accidents into lour types - 'especially important accident', 'important accident', 'ordinary accident', and 'minor accident' - by the Gray Clustering Method. It is lound that the crew's negligence accounts for 93.5% olthe causelor all accidents. Furthermore, 85.1% of crews negligence is caused by senior crew. Based on above findings, some suggestions are provided. It is obvious that the results of this study can strengthen the seaman's ability to deal with an emergency accident. The Grey Clustering Method proposed in this study is also helpful for organizations, such as the admiralty court and the salvage organization, in optimizing the level of resources to invest.
Relation: 16(4),P379-413
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/37543
Appears in Collections:[航運管理學系] 期刊論文

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