کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8065047 | 1520679 | 2016 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A risk assessment approach to improve the resilience of a seaport system using Bayesian networks
ترجمه فارسی عنوان
رویکرد ارزیابی ریسک برای بهبود قابلیت انعطاف پذیری یک سیستم دریایی با استفاده از شبکه های بیزی
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کلمات کلیدی
سیستم های دریایی، مدل پشتیبانی تصمیم شبکه اعتقادات بیزی تئوری مجموعه فازی انعطاف پذیری، تجزیه و تحلیل میزان حساسیت،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی دریا (اقیانوس)
چکیده انگلیسی
Over the years, many efforts have been focused on developing methods to design seaport systems, yet disruption still occur because of various human, technical and random natural events. Much of the available data to design these systems are highly uncertain and difficult to obtain due to the number of events with vague and imprecise parameters that need to be modelled. A systematic approach that handles both quantitative and qualitative data, as well as means of updating existing information when new knowledge becomes available is required. Resilience, which is the ability of complex systems to recover quickly after severe disruptions, has been recognised as an important characteristic of maritime operations. This paper presents a modelling approach that employs Bayesian belief networks to model various influencing variables in a seaport system. The use of Bayesian belief networks allows the influencing variables to be represented in a hierarchical structure for collaborative design and modelling of the system. Fuzzy Analytical Hierarchy Process (FAHP) is utilised to evaluate the relative influence of each influencing variable. It is envisaged that the proposed methodology could provide safety analysts with a flexible tool to implement strategies that would contribute to the resilience of maritime systems.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ocean Engineering - Volume 111, 1 January 2016, Pages 136-147
Journal: Ocean Engineering - Volume 111, 1 January 2016, Pages 136-147
نویسندگان
Andrew John, Zaili Yang, Ramin Riahi, Jin Wang,