Ship route simulation based on the cluster analysis
https://doi.org/10.21821/2309-5180-2023-15-5-735-743
Abstract
The problem of safe ship’s route planning at the variable hydrometeorological situation along the route is considered in the paper. The problem solved in the paper is based on the division of the water area into separate clusters, depending on its characteristics. The route from Busan Port to Kushiro Port is used as an example. The specifics of this route is that it runs through the open sea, and through the straits and archipelagos. The aim of the work is to automate the process of planning the route and adjusting it during the trip, depending on changes in external conditions. The graph theory for modeling a route is proposed in this paper. The construction of graphs is implemented using the cluster analysis method. In the analysis, the water area of the route is divided into separate subareas, depending on the distance to the coast and the depths difference. Open water areas are separated into larger clusters. Near the coast and at shallow depths, clustering is shorter. The cluster centroids are the vertices of the graphs of the future route. As result it is a simulation of graphs of different sizes. The union of graphs forms the hypergraph. The distance is used as the weight of the graph edges. To determine the most preferable route in criteria of speed, cost or safety, weights are added depending on weather and other factors. As a result of this approach, several routes are planning on the hypergraph. Depending on the weight of the priority criteria, a route is selected automatically. The proposed method can be used to create systems for automated planning of optimal routes, taking into account the selected criteria under changing environmental conditions in the process of voyage and replanning it if necessary.
About the Authors
D. A. Akmaykin
Maritime State University named after admiral G. I. Nevelskoy
Russian Federation
Russian Federation
Akmaуkin, Denis A. - PhD, associate professor
50a Verkhneportovaya Str., Vladivostok, 690003
V. V. Bocharova
Maritime State University named after admiral G. I. Nevelskoy
Russian Federation
Russian Federation
Bocharova, Victoria V. - PhD
50a Verkhneportovaya Str., Vladivostok, 690003
S. F. Klyueva
Maritime State University named after admiral G. I. Nevelskoy
Russian Federation
Russian Federation
Klyueva, Svetlana F. - PhD
50a Verkhneportovaya Str., Vladivostok, 690003
References
1. Akmaуkin, D. A., V. V. Bocharova, and A. V. Gams. “Route planning.” Ekspluatatsiya morskogo transporta 1(106) (2023): 50–54.
2. Mezentseva, L. I., and I. S. Karpushin. Praktikum po gidrometeorologicheskomu obespecheniyu sudovozhdeniya. Chast’ 2. Sinopticheskaya meteorologiya dlya sudovoditelei. Vladivostok: Dal’rybvtuz, 2022.
3. Panov, B. N. Gidrometeorologicheskoe obespechenie sudovozhdeniya. Kerch’: Kerchenskii gosudarstvennyi morskoi tekhnologicheskii universitet, 2020.
4. Sukhina, M. I., G. V. Belokur, and A. V. Golovko. Gidrometeorologicheskoe obespechenie sudovozhdeniya. M.: INFRA-M, 2022.
5. Gilev, Yu. S., S. A. Vereshchagin, D. N. Rubinshtein, and V. N. Paseshnichenko. Korablevozhdenie. Vladivostok: TOVMI im. S. O. Makarova, 2009.
6. Chelton, Dudley B., and Michael H. Freilich. “Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models.” Monthly Weather Review 133.2 (2005): 409–429. DOI: 10.1175/MWR-2861.1
7. Chelton, Dudley B., Michael H. Freilich, Joseph M. Sienkiewicz, and Joan M. Von Ahn. “On the use of QuikSCAT scatterometer measurements of surface winds for marine weather prediction.” Monthly weather review 134.8 (2006): 2055–2071. DOI: 10.1175/MWR3179.1
8. Risien, Craig M., and Dudley B. Chelton. “A satellite-derived climatology of global ocean winds.” Remote Sensing of Environment 105.3 (2006): 221–236. DOI: 10.1016/j.rse.2006.06.017.
9. Aleksandrov, A. G. Optimal’nye i adaptivnye sistemy. M.: Vysshaya shkola, 1989.
10. Galeev, E. M., and V. M. Tikhomirov. Optimizatsiya: teoriya, primery, zadachi. M.: Editoriyal URSS, 2000.
11. Moiseev, N. N. Chislennye metody v teorii optimal’nykh sistem. M.: Nauka, 1971.
12. Akmaikin, D. A., S. F. Klyueva, and P. A. Salyuk. “Proekt sistemy operativnogo analiza i optimizatsii dvizheniya morskikh sudov.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 1(29) (2015): 229–236. DOI: 10.21821/2309-5180-2015-7-1-229-236.
13. Vas’kov, A. S., and A. A. Mironenko. “Analiz i vybor metodov avtomatizirovannogo poiska optimal’nogo marshruta v navigatsionnykh kompleksakh.” Sb. nauchn. tr. NGMA 2 (1997): 103–119.
14. Vaskov, V. A., and A. A. Mironenko. “Designing of the program trajectory of the vessel maneuvering at mooring.” Ekspluatatsiya morskogo transporta 4 (58) (2009): 25–29.
15. Akmaykin, Denis A., Dmitriy B. Homenko, Pavel A. Salyuk, Igor E. Stepochkin, and Konstantin A. Shmirko. “Solaris’ information system for ship’s navigation, using operational analysis of shipboard and satellite remote sensing data of hydrosphere and atmosphere.” Ocean Remote Sensing and Monitoring from Space. Vol. 9261. SPIE, 2014. 201–210. DOI: 10.1117/12.2069007.
16. Vagushchenko, L. L. Sudovye navigatsionno-informatsionnye sistemy. Odessa: Feniks, 2004.
17. Deryabin, V. V. Planirovanie perekhoda v elektronnykh kartograficheskikh navigatsionnykh informatsionnykh sistemakh (EKNIS). SPb.: Naukoemkie tekhnologii, 2022.
18. Akmaikin, D. A., S. F. Klyueva, and P. A. Salyuk. “Rezul’taty issledovanii problemy modelirovaniya grafa marshruta sudna na osnove algoritmov klasterizatsii.” Vestnik gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 5(39) (2016): 29–38. DOI: 10.21821/2309-5180-2016-8-5-29-38.
19. Kutuzov, V. M., A. A. Konovalov, and V. N. Mikhailov. Morskaya radiolokatsiya: konspekt lektsii. SPb: SPbGETU “LETI”, 2016.
20. Dun, S. “Opredelenie ploshchadi i plecha parusnosti sudna-gazovoza LNG.” Trudy NGTU im. R. E. Alekseeva 4(111) (2015): 218–221.
Review
For citations:
Akmaykin D.A., Bocharova V.V., Klyueva S.F. Ship route simulation based on the cluster analysis. Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova. 2023;15(5):735-743. (In Russ.) https://doi.org/10.21821/2309-5180-2023-15-5-735-743
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