Document Type: Original Article
Health, Safety and Environment (HSE) Department, University of Tehran.
Assistant Professor, Graduate Faculty of Environment, University of Tehran.
Gas Transmission Operation District 8, Iranian Gas Transmission Company, Iran.
PhD Student of Environmental Planning, Graduate Faculty of Environment, University of Tehran.
Risk assessment is the heart of ISO and OHSAS auditions and also is vital demand
for any industry to characterize hazards and their risks for personnel, environment
and loss of money. Traditionally, Risk matrix was a very useful tool to estimate the
risk of process or equipment or acts that helps decision-making processes.
Establishment and development of soft set theory and its applications are used in
recent years and are extended in combined forecasting, decision-making,
information science and so on. Fuzzy modeling is one of the most powerful tools to
estimate relation between input-output of nonlinear systems. In this method, fuzzy
numbers are referred to variables that express uncertainties. A fuzzy number
expresses relation between an imprecise or uncertain number, X and a membership
function, ì that is between (0,1). In other words, the fuzzy logic tool provides a
technique to deal with imprecision and information, the fuzzy theory provides a
mechanism for representing linguistic constructs such as “many”, “low”,
“medium”, “few”, etc. In the new view of analysts and decision makers, risk
analysis is being done with great uncertainties because risk assessment requires
detail information about damage frequency rate of particular processes and
equipment components. This data usually are imprecise and uncertain. One of the
advantages of fuzzy logic in the field of risk assessment is dealing with these