• P. S. Nosov Kherson State Maritime Academy, Ukraine.
  • V. V. Cherniavskyi Kherson State Maritime Academy, Ukraine.
  • S. M. Zinchenko Kherson State Maritime Academy, Ukraine.
  • I. S. Popovych Kherson State University, Ukraine.
  • Ya. А. Nahrybelnyi Kherson State Maritime Academy, Ukraine.
  • H. V. Nosova Kherson Polytechnic Special College of Odessa National Polytechnic University, Ukraine.



reaction identification systems, automated data processing systems, simulation of operator reactions, computer navigation simulators, analysis of the human factor, automated control systems.


Context. The article introduces an approach for analyzing the reactions of a marine electronic navigation operator as well as automated identification of the likelihood of the negative impact of the human factors in ergatic control systems for sea transport. To meet the target algorithms for providing information referring to the results of human-machine interaction of an operator in marine emergency response situations while managing increasing complexity of navigation operations’ carrying out are put forward.

Objective. The approach delivers conversion of the operator’s actions feature space into a logical-geometric one of p-adic systems making the level of the operator’s intellectual activity by using automated means highly likely to be identified. It is sure to contribute to its dynamic prediction for the sake of further marine emergency situations lessening.

Method. Within the framework of the mentioned above approach attaining objective as automated identification of the segmented results of human-machine interactions a method for transforming deterministic fragments of an operator’s intellectual activity in terms of p-adic structures is proposed to be used. To cope with such principles as specification, generalization as well as transitions to different perception spaces of the navigation situation by the operator are said to be formally specified. Having been carried out of simulation modeling has turned out to confirm the feasibility of the proposed above approach causing, on the grounds of temporary identifiers, the individual structure of the operator’s reactions to be determined. As a result, the data obtained has delivered the possibility of having typical situations forecasted by using automated multicriteria methods and tools. This issue for its part is said to be spotted as identification of individual indicators of the operator’s reaction dynamics in complex man-machine interaction.

Results. In order to have the proposed formal-algorithmic approach approved an experiment was performed using the navigation simulator Navi Trainer 5000 (NTPRO 5000). Automated analysis of experimental server and video data have furnished the means of deterministic operator actions identification in the form of metadata of the trajectory of his reactions within the space of p-adic structures. Thus, the results of modeling involving automated neural networks are sure to facilitate the time series of the intellectual activity of the electronic marine navigation operator to be identified and, therefore, to predict further reactions with a high degree of reliability.

Conclusions. The proposed formal research approaches combined with the developed automated means as well as algorithmic and methodological suggestions brought closer to the objectives for solving the problem of automated identification of the negative impact of the human factors of the electronic navigation operator on a whole new level. The efficiency of the proposed approach is noticed to have been approved by the results of automated processing of experimental data and built forecasts.

Author Biographies

P. S. Nosov , Kherson State Maritime Academy, Ukraine.

PhD, Associate Professor of Navigation Department.

V. V. Cherniavskyi , Kherson State Maritime Academy, Ukraine.

Dr. Sc., Professor, Rector.

S. M. Zinchenko , Kherson State Maritime Academy, Ukraine.

PhD, Senior Lecturer of Ship Handling Department, head of the laboratory of electronic simulators.

I. S. Popovych , Kherson State University, Ukraine.

Dr. Sc., Professor of the Department of General and Social Psychology.

Ya. А. Nahrybelnyi , Kherson State Maritime Academy, Ukraine.

Dr. Sc., Associate Professor, Dean of the Department of Navigation.

H. V. Nosova , Kherson Polytechnic Special College of Odessa National Polytechnic University, Ukraine.

Senior Lecturer of Computer and software engineering Department.


Perera L. P. Deep learning toward autonomous ship navigation and possible COLREGs failures, Offshore Mech, 2020, Vol. 142, 031102. DOI: 10.1115/1.4045372.

Bakdi A., Glad I. K., Vanem E., et al. AIS-Based multiple vessel collision and grounding risk sdentification based on adaptive safety domain, J. Mar. Sci. Eng, 2020, Vol. 8, P. 5. DOI: 10.3390/jmse8010005.

Shen H., Guo C., Li T. et al. An intelligent collision avoidance and navigation approach of unmanned surface vessel considering navigation experience and rules, Journal of Harbin Engineering University, 2018, Vol. 39, pp. 998– 1005. DOI: 10.11990/jheu.201711024.

Hwang Soojin. Development of safety index for evaluation of ship navigation, Journal of Korean navigation and port research, 2014, Vol. 38, pp. 203–209. DOI: 10.5394/KINPR.2014.38.3.203.

Shevchenko R., Popovych I., Spytska L. et al. Comparative analysis of emotional personality traits of the students of maritime science majors caused by long-term staying at sea, Revista Inclusiones, 2020, Vol. 7, pp. 538–554.

Ferguson T. A course in game theory, USA, 2020. – 408 p.

Terence R., Friedberg A. A conjecture on the nature and evolution of consciousness, Neuropsychoanalysis, 2016, Vol. 18, pp. 1–43. DOI: 10.1080/15294145.2016.1240045.

Kasianov V. O., Prokopenko O. Ye., Shipityak T. V. Dvorivneva model` generacziyi perevag, Eastern-European Journal of Enterprise Technologies, 2011, Vol. 50, pp. 35– 40.

Hu G., Li J., Tang R. The revealed preference theory of stable matchings with one-sided preferences, Games and Economic Behavior, 2020, Vol. 124, pp. 305–318. DOI: 10.1016/j.geb.2020.08.015.

Subbotin S. A. Methods of synthesis of models of quantitative dependencies in the basis of trees of regression, realizing cluster – regression approximation by precedents, Radio Electronics, Computer Science, Control, 2019, Vol. 3, pp. 76–85. DOI: 10.15588/1607-3274-2019-3-9.

Kasana H. S. Introductory operations research. Theory and applications, Springer, 2004, 580 p.

Balaguer M. Mathematical Pluralism and Platonism, Journal of Indian Council of Philosophical Research, 2017, Vol. 34, pp. 379–398. DOI: 10.1007/s40961-016-0084-4.

Xie S., Li Y., Wang W. et al. Assessment of UAV’s operator cognitive state based on behavior signals, Journal of Northwestern Polytechnical University, 2018, Vol. 36, pp. 715–721. DOI: 10.1051/jnwpu/20183640715.

Nosov P., Ben A., Safonova A. et al. Approaches going to determination periods of the human factor of navigators during supernumerary situations, Radio Electronics, Computer Science, Control, 2019, Vol. 2, pp. 140–150. DOI: 10.15588/1607-3274-2019-2-15.

Mao R., Li G., Hildre H. P. et al. Analysis and evaluation of eye behavior for marine operation training, Journal of Eye Movement Research, 2019, Vol. 12. DOI: 10.16910/jemr.12.3.6.

Yasseri S., Bahai H. Safety in Marine Operations, International Journal of coastal and offshore engineering, 2018, Vol. 2, pp. 29–40. DOI: 10.29252/ijcoe.2.3.29.

Bruijn W., Rip J., Hendriks A.J.H. et al. Probabilistic downtime estimation for sequential marine operations, Applied Ocean Research, 2019, Vol. 1, pp. 257–267. DOI: 10.1016/j.apor.2019.02.014.

Paterson J., Thies P., Sueur R. et al. Assessing marine operations with a Markov-switching autoregressive metocean model, Journal of Engineering for the Maritime Environment, 2020, Vol. 234, pp. 785–802. DOI: 10.1177/1475090220916084.

Khrennikov A., Nilson M. Theory of P-Adic Valued Probability. In: P-adic Deterministic and Random Dynamics, Mathematics and Its Applications, 2004, Vol. 574. DOI: 10.1007/978-1-4020-2660-7_13.

Zinchenko S., Nosov P., Mateichuk V. et al. Automatic collision avoidance system with many targets, including maneuvering ones, Bulletin of University of Karaganda. Technical Physics, 2019, Vol. 96. pp. 69–79. DOI: 10.31489/2019Ph4/69-79.

Zinchenko S. M., Ben A. P., Nosov P. S. et al. Improving the Accuracy and Reliability of Automatic Vessel Moution Control System, Radio Electronics, Computer Science, Control, 2020, Vol. 2. pp. 183–195. DOI: 10.15588/1607-32742020-2-19.

Prokopchuk Y.A. Sketch of the Formal Theory of Creativity. Dnepr, PSACEA Press, 2017, 452 p.

Harris M. Speculations on the mod p representation theory of p-adic groups, Annales de la faculté des sciences de Toulouse Mathématiques, 2016, Vol. 25. pp. 403–418. DOI: 10.5802/afst.1499.

Kasianov V. Subjective entropy of preferences. Subjective analysis. Warsaw, Poland: Institute of aviation, 2013, 644 p.

Nosov P.S., Zinchenko S.M., Popovych I.S. et al. Diagnostic system of perception of navigation danger when implementation complicated maneuvers, Radio Electronics, Computer Science, Control, 2020, Vol. 1. pp. 146–161. DOI: 10.15588/1607-3274-2020-1-15.

Nosov P.S., Popovych I.S., Cherniavskyi V.V. et al. Automated identification of an operator anticipation on marine transport, Radio Electronics, Computer Science, Control, 2020, Vol. 3. pp. 158–172. DOI: 10.15588/1607-3274-20203-15.

Nosov P., Palamarchuk I., Zinchenko S. et al. Development of means for experimental identification of navigator attention in ergatic systems of maritime transport, Bulletin of University of Karaganda, 2020, Vol. 97. pp. 58–69. DOI: 10.31489/2020Ph1/58-69.

Kononenko O., Kononenko A., Stynska V. et al. Research of the factor structure of the model of world view setting at a young age, Revista Inclusiones, 2020, Vol. 7. pp. 98–116.

Vagushchenko L.L., Vagushchenko A.A. Enhancement of support for collision avoidance decisions, Shipping & Navigation, 2018, Vol. 27. pp. 24–34. DOI: 10.31653/23065761.27.2018.24-34.

Yang T., Brinton C. G., Joe-Wong C. et al. Behavior-Based Grade Prediction for MOOCs Via Time Series Neural Networks, IEEE Journal of Selected Topics in Signal Processing, 2017, Vol. 11. pp. 716–728. DOI: 10.1109/JSTSP.2017.2700227.




How to Cite

Nosov , P. S., Cherniavskyi , V. V., Zinchenko , S. M., Popovych , I. S., Nahrybelnyi Y. А., & Nosova , H. V. (2021). IDENTIFICATION OF MARINE EMERGENCY RESPONSE OF ELECTRONIC NAVIGATION OPERATOR . Radio Electronics, Computer Science, Control, 1(1), 208–223.

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