Taking into account current trends in the development of ergatic maritime transport systems, the factors of the navigator’s influence on vessel control processes were determined. Within the framework of the research hypothesis, to improve navigation safety, it is necessary to apply predictive data mining models and automated vessel control. The paper proposes a diagram of the ergatic vessel control system and a model for identifying the influence of the navigator “human factor” during navigation. Within the framework of the model based on the principles of navigator decision trees, prediction by data mining means is applied, taking into account the identifiers of the occurrence of a critical situation. Based on the prediction results, a method for optimal vessel control in critical situations was developed, which is triggered at the nodes of the navigator decision tree, which reduces the likelihood of a critical impact on vessel control. The proposed approaches were tested in the research laboratory “Development of decision support systems, ergatic and automated vessel control systems”. The use of the Navi Trainer 5,000 navigation simulator (Wärtsilä Corporation, Finland) and simulation of the navigation safety control system for critical situations have confirmed its effectiveness. As a result of testing, it was determined that the activation of the system allowed reducing the likelihood of critical situations by 18–54 %. In 11 % of cases, the system switched the vessel control processes to automatic mode and, as a result, reduced the risk of emergencies. The use of automated data mining tools made it possible to neutralize the negative influence of the “human factor” of the navigator and to reduce the average maneuvering time during vessel navigation to 23 %

On the basis of empirical experimental data, relationships were identified indicating the influence of navigators' response to such vessel control indicators as maneuverability and safety. This formed a hypothesis about a non-random connection between the navigator's actions, response and parameters of maritime transport management. Within the framework of this hypothesis, logical-formal approaches were proposed that allow using server data of both maritime simulators and operating vessels in order to timely identify the occurrence of a critical situation with possible catastrophic consequences. A method for processing navigation data based on the analysis of temporal zones is proposed, which made it possible to prevent manifestations of reduced efficiency of maritime transport management by 22.5 %. Based on cluster analysis and automated neural networks, it was possible to identify temporary vessel control fragments and classify them by the level of danger. At the same time, the neural network test error was only 3.1 %, and the learning error was 3.8 %, which ensures the high quality of simulation results. The proposed approaches were tested using the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland). The simulation of the system for identifying critical situations in maritime transport management made it possible to reduce the probability of catastrophic situations by 13.5 %. The use of automated artificial neural networks allowed defining critical situations in real time from the database of maritime transport management on the captain's bridge for an individual navigator.

This article presents the development of a modular software suite for automated analysis of scientific publications in PDF format. The system integrates vectorization, clustering, topic modelling, dimensionality reduction, and fuzzy logic to combine both formal (vector-based) and semantic (topic-based) approaches. Interactive 3D visualization supports intuitive exploration of thematic clusters, allowing users to highlight relevant documents and adjust analytical parameters. Validation on a maritime safety case study confirmed the system’s ability to process large publication collections, identify relevant sources, and reveal underlying knowledge structures. Compared to established frameworks such as PRISMA or Scopus/WoS Analytics, the proposed tool operates directly on full-text content, provides deeper thematic classification, and does not require subscription-based databases. The study also addresses the limitations arising from data bias and reproducibility issues in the semantic interpretability of safety-critical decision-making systems. The approach offers practical value for organizations in safety-critical domains—including transportation, energy, cybersecurity, and human–machine interaction—where rapid access to thematically related research is essential.

The object of this study is the safety control system of ship management, by identifying and restoring the qualification parameters of shipmasters in critical situations. The task solved in the study is the timely determination of an insufficient level of qualification for the performance of certain operations in controlling the movement of the ship, by applying a formal-logical model of detecting the intuitive actions of the operator-shipmaster and gradually restoring his/her qualification parameters using the devised method. The stages of development and the formal-logical structure of the model and method in terms of cognitive automation were described in detail as the study results. It was possible to ensure early detection of risks when controlling the movement of the ship in 56 % of cases, during a laboratory experiment on simulators, which in 24 % of cases turned out to be particularly dangerous. The interpretation of the results involved algorithmizing complex and formalized data on the actions of operators and the application of the method of restoring their qualification parameters, which allowed a comprehensive approach to safety management. The distinguishing features of the findings were to predict the level of danger by simulating maritime operations with input navigational and individual conditions. This made it possible to improve the effectiveness of operations to 89 %, reduce the phenomenon of loss of control over the course to 32 %, reduce critical situations to 7 % and the cost of resources. The scope and conditions of practical use involve a comprehensive assessment of external and internal influences on the level of danger, delay in decision-making by operators, as well as sailing conditions. The simulation results could be used to devise strategies for planning maneuvers, predicting risks, and developing maritime security systems Об'єктом дослідження є системи управління безпекою керування судном, шляхом ідентифікації та відновлення кваліфікаційних параметрів судноводіїв у критичних ситуаціях. Проблема, що вирішувалася у даному дослідженні, полягає у передчасному визначенні недостатнього рівня кваліфікації для виконання окремих операцій при управлінні рухом судна, шляхом застосування формально-логічної моделі виявлення інтуїтивних дій оператора-судноводія та поетапним відновленням його кваліфікаційних параметрів за допомогою розробленого методу. У якості отриманих результатів було детально описано етапи розробки та формально-логічну структуру моделі та методу в розрізі когнітивної автоматизації. Вдалось забезпечити завчасне виявлення ризиків при керуванні рухом судна в 56 % випадків, підчас лабораторного експерименту на симуляторах що у 24 % випадків виявились особливо небезпечними. Інтерпретація результатів полягала в алгоритмізації складно-формалізованих даних про дії операторів та застосуванні методу відновлення їх кваліфікаційних параметрів що дозволило комплексно підійти до управління безпекою. Особливості та відмінні риси результатів полягали у прогнозуванні рівня небезпеки шляхом моделювання морських операцій із вхідними навігаційними та індивідуальними умовами. Це дозволило збільшити результативність виконання операцій до 89 %, зменшити явище втрати контролю над курсом до 32 %, скоротити критичні ситуації до 7 % та витрати ресурсів. Сфера та умови практичного використання полягає у комплексній оцінці зовнішніх та внутрішніх впливів на рівень небезпеки, затримки у прийнятті рішень операторами та умов плавання. Результати моделювання можуть бути використані для створення стратегій планування маневрів, прогнозування ризиків та розробці систем морської безпеки