Abstract

Fuzzy risk analysis plays an important role in mitigating the levels of harm of a risk. In real world scenarios, it is a big challenge for risk analysts to make a proper and comprehensive decision when coping with risks that are incomplete, vague and fuzzy. Many established fuzzy risk analysis approaches do not have the flexibility to deal with knowledge in the form of preferences elicitation which lead to incorrect risk decision. The inefficiency is reflected when they consider only risk analyst preferences elicitation that is partially known. Nonetheless, the preferences elicited by the risk analyst are often non-homogeneous in nature such that they can be completely known, completely unknown, partially known and partially unknown. In this case, established fuzzy risk analysis methods are considered as inefficient in handling risk, hence an appropriate fuzzy risk analysis method that can deal with the non-homogeneous nature of risk analyst’s preferences elicitation is worth developing. Therefore, this paper proposes a novel fuzzy risk analysis method that is capable to deal with the non-homogeneous risk analyst’s preferences elicitation based on grey numbers. The proposed method aims at resolving the uncertain interactions between homogeneous and non-homogeneous natures of risk analyst’s preferences elicitation by using a novel consensus reaching approach that involves transformation of grey numbers into grey parametric fuzzy numbers. Later on, a novel fuzzy risk assessment score approach is presented to correctly evaluate and distinguish the levels of harm of the risks faced, such that these evaluations are consistent with preferences elicitation of the risk analyst. A real world risk analysis problem in fiber industry is then carried out to demonstrate the novelty, validity and feasibility of the proposed method.

中文翻译：

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纤维行业非均质偏好引发影响下的模糊风险分析

摘要

模糊风险分析在减轻风险危害程度方面起着重要作用。在现实世界中，应对不完整，模糊和模糊的风险对于风险分析师来说是一个巨大的挑战，要做出正确而全面的决策。许多已建立的模糊风险分析方法都没有灵活性，无法以偏好启发的形式处理知识，从而导致错误的风险决策。当他们仅考虑部分已知的风险分析师偏好引发时，就会反映出效率低下。但是，风险分析师引起的偏好通常在本质上是不统一的，因此它们可以是完全已知，完全未知，部分已知和部分未知的。在这种情况下，已建立的模糊风险分析方法被认为无法有效处理风险，因此，值得开发一种能够处理风险分析师偏好偏好的非均质性的模糊风险分析方法。因此，本文提出了一种新颖的模糊风险分析方法，该方法能够处理基于灰度数的非均质风险分析师的偏好诱导。所提出的方法旨在通过使用一种将灰阶数转换为灰阶参量模糊数的新颖的共识达成方法，解决风险分析师偏好偏好的同质和非同质性质之间的不确定相互作用。后来，提出了一种新颖的模糊风险评估评分方法，可以正确评估和区分所面临风险的危害程度，从而使这些评估与风险分析师的偏好形成一致。