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Machine learning models and methods for solving optimization and forecasting problems of the work of seaports

https://doi.org/10.37661/1816-0301-2022-19-4-94-110

Abstract

Machine learning techniques have made significant advances and expanded application sphere over the past decade to include problems of port operations. This happened due to the growing amount of data available cargo ports. We review the literature on models and methods of machine learning and their application to optimization of port operations. A special attention is paid to the port planning and development a wide range of topics in port operations, including port planning and development, their safety and security, water and land port operations.

About the Authors

M. N. Lukashevich
Belarusian State University
Belarus

Mikhail N. Lukashevich, Postgraduate Student, the Faculty of Applied Mathematics and Computer Science

av. Nezavisimosti, 4, Minsk, 220050



M. Y. Kovalyov
The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
Belarus

Mikhail Y. Kovalyov, Corresponding Member of the National Academy of Sciences of Belarus

st. Surganova, 6, Minsk, 220012



References

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Review

For citations:


Lukashevich M.N., Kovalyov M.Y. Machine learning models and methods for solving optimization and forecasting problems of the work of seaports. Informatics. 2022;19(4):94-110. (In Russ.) https://doi.org/10.37661/1816-0301-2022-19-4-94-110

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This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 1816-0301 (Print)
ISSN 2617-6963 (Online)