Dynamic Fuzzy Logic Model for Risk Assessment of Marine Crude Oil Transportation

As a scarce strategic resource, crude oil is closely intertwined with national strategies, global policies, international relationships, and national competence. Unbalanced demand and production of crude oil lead to huge amounts of import and export activities. Marine transportation accounts for about 80% of the total oil transport because of the low cost. However, it also incurs an extremely high risk in doing so. Therefore, it is significantly important to assess and control risk effectively in crude oil transportation. In risk assessment, uncertainty evaluation becomes a key variable that cannot be neglected. Previous cases show that fuzzy logic can be applied to manage uncertainty. However, the use of fuzzy logic usually encounters two difficulties: determination of the membership functions and establishment of the reference machine. This paper presents a dynamic fuzzy logic model (DFLM) that can improve the stated problems. The DFLM is developed from fuzzy theory and an incident causation model. The model is examined with a hypothetical case. Preliminary results show that the model reduces the time of risk assessment and increases the reliability of evaluation.