Meteorological Risk Assessment Based on Fuzzy Logic Systems for Maritime

Abstract

In recent years, numerous casualties have been associated with a lack of safe navigation of ships. Despite advanced navigation systems and the implementation of safety management systems onboard ships, maritime safety is still one of the major concerns for the shipping industry. This research proposes a proactive modeling approach that utilizes Fuzzy Logic and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). The model primarily provides continuous meteorological risk assessment for ships to improve marine navigational safety. In the study, Wind Speed, Sea Conditions, Visibility, and Day/Night Ratio are converted to meteorological risk factors using meteorological risk assessment system. Supported by ANFIS, the meteorological risk assessment system has demonstrated that the database contains details of over 180 marine casualty information involving navigation and traffic accidents. The results emphasize that environmental factors, as well as the Day/Night Ratio, significantly influence ship navigational safety. Hence, a meteorological risk assessment system can enhance navigational safety and prevent loss of life in the shipping industry. As a result, a meteorological risk assessment framework has enormous potential for preventing accidents and improving the safety and sustainability of the shipping industry. In this regard, the proposed model is a one-of-a-kind framework that will be extremely useful for mitigating and preventing the effects of maritime accidents.

Keywords

• decision support system
• fuzzy logic
• maritime accident dataset
• meteorological risk assessment
• ship navigation safety