METHOD OF AUTOMATED IDENTIFICATION OF QUALIFICATION PARAMETERS FOR MARINE OPERATORS UNDER RISK CONDITIONS
https://doi.org/10.33815/2313-4763.2023.1-2.26-27.144-165
Abstract
The objective of the study is to enhance maritime safety by applying a method for identifying and predicting the qualification parameters of ship operators based on fuzzy logic. The core challenge of this research lies in the necessity to control internal uncertainty factors of ship operator actions and develop a system that identifies their qualification parameters to ensure safe decision-making in complex navigational conditions.
The research methodology comprises: a) an algorithm for automatic data processing of ECDIS to reduce subjectivity in defining fuzzy membership functions related to navigational factors; b) formalization of the structure of fuzzy functions and establishment of a rule base for identifying risks in complex navigation scenarios; and c) simulation-based fuzzy modeling that investigates the influence of qualification parameters on the overall risk index of ship motion management.
The research outcomes involve the development of an intelligent system predicting navigational risks in intricate maritime conditions. Through simulation modeling, it has been identified that ship operators' qualification parameters significantly impact the risk associated with vessel management. For instance, an increase in parameters across four indicators can elevate the overall risk by 15.8%, shifting the situation into a hazardous or critical category.
The practical significance is manifested by the efficiency of automated ECDIS data processing, which reduced subjective errors and refined navigational risk prediction. The revealed influence of ship operators' qualification parameters on risk levels underscores the importance of individualized forecasts tailored to each operator. The practical value also lies in the potential to enhance maritime safety by precise risk prediction and management, considering the human factor of each operator. Future research will focus on integrating this method into other ship motion management systems, creating even more effective decision-support tools for operators under conditions of inherent uncertainty. Bibl. 23 fig. 19.
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