Quantifying Uncertainty in Risk Assessment using Fuzzy Theory

by   Hengameh Fakhravar, et al.

Risk specialists are trying to understand risk better and use complex models for risk assessment, while many risks are not yet well understood. The lack of empirical data and complex causal and outcome relationships make it difficult to estimate the degree to which certain risk types are exposed. Traditional risk models are based on classical set theory. In comparison, fuzzy logic models are built on fuzzy set theory and are useful for analyzing risks with insufficient knowledge or inaccurate data. Fuzzy logic systems help to make large-scale risk management frameworks more simple. For risks that do not have an appropriate probability model, a fuzzy logic system can help model the cause and effect relationships, assess the level of risk exposure, rank key risks in a consistent way, and consider available data and experts'opinions. Besides, in fuzzy logic systems, some rules explicitly explain the connection, dependence, and relationships between model factors. This can help identify risk mitigation solutions. Resources can be used to mitigate risks with very high levels of exposure and relatively low hedging costs. Fuzzy set and fuzzy logic models can be used with Bayesian and other types of method recognition and decision models, including artificial neural networks and decision tree models. These developed models have the potential to solve difficult risk assessment problems. This research paper explores areas in which fuzzy logic models can be used to improve risk assessment and risk decision making. We will discuss the methodology, framework, and process of using fuzzy logic systems in risk assessment.


page 20

page 24


Conflict Analysis for Pythagorean Fuzzy Information Systems with Group Decision Making

Pythagorean fuzzy sets provide stronger ability than intuitionistic fuzz...

Reliability Assessment of Distribution System Using Fuzzy Logic for Modelling of Transformer and Line Uncertainties

Reliability assessment of distribution system, based on historical data ...

Machine Reasoning to Assess Pandemics Risks: Case of USS Theodore Roosevelt

Assessment of risks of pandemics to communities and workplaces requires ...

An Application of D-vine Regression for the Identification of Risky Flights in Runway Overrun

In aviation safety, runway overruns are of great importance because they...

A framework for spatial heat risk assessment using a generalized similarity measure

In this study, we develop a novel framework to assess health risks due t...

Terrorism Event Classification Using Fuzzy Inference Systems

Terrorism has led to many problems in Thai societies, not only property ...