Developing an effective fuzzy logic model for managing risks in marine oil transport

The marine oil transport system calls for a long‐term safety precaution mechanism for the continuous growth of the transport scale. Fuzzy logic, as a generally accepted method in risk management, is good at handling ambiguous description. However, traditional fuzzy logic has difficulties in determining the membership functions and the inference machine, especially under conditions of changing surroundings. This paper develops an improved fuzzy logic model, which is able to solve the above‐mentioned problems. The model improves the normal fuzzy expert system through three loops: proactive, reactive and database improvement. The effectiveness of the improved model is demonstrated by the comparison of two scenarios of a marine oil transport case. The results show that the model can decrease the response time to external events and increase the accuracy of risk assessment.