当前位置: X-MOL 学术Cybern. Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Modeling Aleatory and Epistemic Uncertainty in Human Health Risk Assessment
Cybernetics and Systems ( IF 1.7 ) Pub Date : 2020-02-08 , DOI: 10.1080/01969722.2020.1722909
Palash Dutta 1
Affiliation  

Abstract Risk plays an important role in the decision making process. To assess the severity and likelihood of impairment to human health from exposure to a substance or activity that under plausible circumstances can cause harm to human health is the main purpose of risk assessment. It is important to know the nature and characteristic of all available information, data or model parameters which are more generally tainted with aleatory and epistemic uncertainty or both type of uncertainty. In some situation, model parameters are affected by aleatory uncertainty and simultaneously other some parameters are affected by epistemic uncertainty, how far computation of the risk is concern, two ways to deal with the situation either transform all the uncertainties to one type of format or need for joint propagation of uncertainties. In this paper, an effort has been made to combine probability distributions, generalized fuzzy numbers, normal fuzzy numbers and generalized interval valued fuzzy numbers within the same framework.

中文翻译:

模拟人类健康风险评估中的偶然和认知不确定性

摘要 风险在决策过程中起着重要作用。风险评估的主要目的是评估暴露于可能对人类健康造成危害的物质或活动对人类健康造成损害的严重程度和可能性。了解所有可用信息、数据或模型参数的性质和特征很重要,这些信息、数据或模型参数通常都带有偶然性和认知不确定性或两种类型的不确定性。在某些情况下,模型参数受偶然不确定性的影响,同时其他一些参数受认知不确定性的影响,风险的计算涉及多远,处理这种情况的两种方法要么将所有不确定性转换为一种格式,要么需要用于不确定性的联合传播。在本文中,
更新日期:2020-02-08
down
wechat
bug