scholarly journals Withdrawal notice to “Fuzzy Bayesian network based on an improved similarity aggregation method for risk assessment of storage tank accident” [PSEP 144 (2020) 242–252]

2021 ◽  
Vol 149 ◽  
pp. 1031
Author(s):  
Xiaoxue Guo ◽  
Ji Jie ◽  
Faisal Khan ◽  
Long Ding
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Storage Tank ◽  
Aggregation Method

scholarly journals Development of a Bayesian network for probabilistic risk assessment of pesticides

2021 ◽  
Author(s):  
Sophie Mentzel ◽  
Merete Grung ◽  
Knut Erik Tollefsen ◽  
Marianne Stenrod ◽  
Karina Petersen ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Environmental Risk ◽  
Environmental Risk Assessment ◽  
Probability Distributions ◽  
Probabilistic Approach ◽  
Probabilistic Risk Assessment ◽  
Risk Calculation ◽  
Link Information ◽  
Probabilistic Risk

Conventional environmental risk assessment of chemicals is based on a calculated risk quotient, representing the ratio of exposure to effects of the chemical, in combination with assessment factors to account for uncertainty. Probabilistic risk assessment approaches can offer more transparency, by using probability distributions for exposure and/or effects to account for variability and uncertainty. In this study, a probabilistic approach using Bayesian network (BN) modelling is explored as an alternative to traditional risk calculation. BNs can serve as meta-models that link information from several sources and offer a transparent way of incorporating the required characterization of uncertainty for environmental risk assessment. To this end, a BN has been developed and parameterised for the pesticides azoxystrobin, metribuzin, and imidacloprid. We illustrate the development from deterministic (traditional) risk calculation, via intermediate versions, to fully probabilistic risk characterisation using azoxystrobin as an example. We also demonstrate seasonal risk calculation for the three pesticides.

A methodology for e-banking risk assessment using fuzzy logic and Bayesian network

2021 ◽  
Vol 19 (3) ◽  
pp. 101-124
Author(s):  
Ako Rita Erhovwo ◽  
Okpako Abugor Ejaita ◽  
Duke Oghorodi
Keyword(s):  
Risk Assessment ◽  
Fuzzy Logic ◽  
Bayesian Network ◽  
Operational Risk ◽  
Assessment Process ◽  
Exposure Level ◽  
Model Assessment ◽  
Assessment Methodology ◽  
Risk Assessment Process ◽  
Risk Assessment Methodology

Risk assessment methodology in general has been around for quite a while, its prominence in the E-banking field is a fairly recent phenomenon. We are at the point where risk assessments are critical to the overall function of banks. Banks are required to assess the processes underlying their operations against potential threats, vulnerabilities, and their potential impact, which helps in revealing the risk exposure level, and the residual risks. Identifying clearly a risk assessment methodology is often the first step of assessing and evaluating risk associated with an organization operation. This paper presents a risk assessment methodology for Ebanking Operational Risk. The proposed risk assessment methodology consists of four major steps: a risk model, assessment approach, analysis approach and a risk assessment process. The main tool of the proposed risk assessment methodology is the risk assessment process. The assessment process gives detailed explanation with respect to which models or techniques may be applied and how they are expressed. In this paper the risk assessment technique is built upon fuzzy logic (FL) concept and Bayesian network (BN). In fuzzy logic, an element is included with a degree of membership. Bayesian network is an inference classifier that is capable of representing conditional independencies. The Bayesian and fuzzy logic–based risk assessment process gives good predictions for risk learning and inference in the E-banking systems. Keywords: Fuzzy logic, Bayesian network, risk assessment methodology, operational risk, Ebanking

Establishment of Risk Assessment Model for Ship Collision using Applied Bayesian Network -Collision Accidents between Fishing vessels and Cargo Vessels -

2015 ◽  
Author(s):  
Takeshi Shinoda ◽  
Koji Uru
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Benefit Analysis ◽  
Fishing Vessels ◽  
Formal Safety Assessment ◽  
Trial Cost

In this study, a risk assessment model for ship collisions is proposed according to the guidelines for Formal Safety Assessment (FSA) approved by IMO in 2002. The analysis is applied to ship collisions between fishing and cargo vessels owing to their high frequency and enormous damage. Bayesian network theory for risk analysis has been applied to reveal a causal relationship on human factors. A trial evaluation of Risk Control Options (RCOs) for collisions is attempted through the calculation of the dominance index. Finally, a trial cost benefit analysis for RCOs is considered through Gross Cost of Averting Fatality (GCAF) in FSA.

Quantitative risk assessment for ammonia ship‐to‐ship bunkering based on Bayesian network

2021 ◽  
Author(s):  
Hongjun Fan ◽  
Hossein Enshaei ◽  
Shantha Gamini Jayasinghe ◽  
Sock Hua Tan ◽  
Chunchang Zhang
Keyword(s):  
Risk Assessment ◽  
Bayesian Network ◽  
Quantitative Risk Assessment
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