{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T20:29:08Z","timestamp":1774470548643,"version":"3.50.1"},"reference-count":27,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2019,1,4]],"date-time":"2019-01-04T00:00:00Z","timestamp":1546560000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Gdynia Maritime University, Poland","award":["446\/DS\/2018"],"award-info":[{"award-number":["446\/DS\/2018"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This article presents safe ship control optimization design for navigator advisory system. Optimal safe ship control is presented as multistage decision-making in a fuzzy environment and as multistep decision-making in a game environment. The navigator\u2019s subjective and the maneuvering parameters are taken under consideration in the model process. A computer simulation of fuzzy neural anticollision (FNAC) and matrix game anticollision (MGAC) algorithms was carried out on MATLAB software on an example of the real navigational situation of passing three encountered ships in the Skagerrak Strait, in good and restricted visibility at sea. The developed solution can be applied in decision-support systems on board a ship.<\/jats:p>","DOI":"10.3390\/rs11010082","type":"journal-article","created":{"date-parts":[[2019,1,4]],"date-time":"2019-01-04T11:34:26Z","timestamp":1546601666000},"page":"82","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Comparison of Computational Intelligence Methods Based on Fuzzy Sets and Game Theory in the Synthesis of Safe Ship Control Based on Information from a Radar ARPA System"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9281-376X","authenticated-orcid":false,"given":"J\u00f3zef","family":"Lisowski","sequence":"first","affiliation":[{"name":"Department of Ship Automation, Gdynia Maritime University, 81-225 Gdynia, Poland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2814-1756","authenticated-orcid":false,"given":"Mostefa","family":"Mohamed-Seghir","sequence":"additional","affiliation":[{"name":"Department of Ship Automation, Gdynia Maritime University, 81-225 Gdynia, Poland"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,4]]},"reference":[{"key":"ref_1","unstructured":"Bist, D.S. (2000). Safety and Security at Sea, Butterworth Heinemann."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kazimierski, W., and Stateczny, A. (2013, January 5\u20137). Fusion of Data from AIS and Tracking Radar for the Needs of ECDIS. Proceedings of the Signal Processing Symposium, Jachranka, Poland.","DOI":"10.1109\/SPS.2013.6623592"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2017\/2561383","article-title":"Inference engine in an intelligent ship course-keeping system","volume":"2017","author":"Borkowski","year":"2017","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"50","DOI":"10.2478\/v10012-012-0023-5","article-title":"Nonlinear observers design for multivariable ship motion control","volume":"19","author":"Tomera","year":"2012","journal-title":"Pol. Marit. Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"117","DOI":"10.12716\/1001.12.01.13","article-title":"Design of an autonomous transport system for coastal areas","volume":"12","author":"Lebkowski","year":"2018","journal-title":"TransNav Int. J. Mar. Navig. Saf. Sea"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kazimierski, W., and Lubczonek, J. (2012, January 23\u201325). Verification of Marine Multiple Model Neural Tracking Filter for the Needs of Shore Radar Stations. Proceedings of the 13 International Radar Symposium, Warsaw, Poland.","DOI":"10.1109\/IRS.2012.6233384"},{"key":"ref_7","first-page":"12","article-title":"Decision making in a fuzzy environment","volume":"17","author":"Bellman","year":"1970","journal-title":"Manag. Sci."},{"key":"ref_8","unstructured":"Isaacs, R. (1965). Differential Games, John Wiley and Sons."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.oceaneng.2016.08.030","article-title":"An analysis of domain-based ship collision risk parameters","volume":"126","author":"Szlapczynski","year":"2016","journal-title":"Ocean Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3","DOI":"10.2478\/v10012-012-0016-4","article-title":"Game control methods in avoidance of ships collision","volume":"19","author":"Lisowski","year":"2012","journal-title":"Pol. Marit. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.procs.2014.08.115","article-title":"The branch-and-bound method, genetic algorithm, and dynamic programming to determine a safe ship trajectory in fuzzy, knowledge-based and intelligent information and engineering systems","volume":"35","year":"2014","journal-title":"Procedia Comput. Sci."},{"key":"ref_12","unstructured":"Modarres, M. (2006). Risk Analysis in Engineering, Taylor and Francis Group."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1111\/j.1934-6093.2001.tb00052.x","article-title":"Neural network based algorithm for dynamic system optimization","volume":"3","author":"Francelin","year":"2001","journal-title":"Asian J. Contr."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Lyu, H., and Yin, Y. (2018). Fast path planning for autonomous ships in restricted waters. Appl. Sci., 12.","DOI":"10.3390\/app8122592"},{"key":"ref_15","unstructured":"Deng, W., Gan, L., Zhou, C., Zheng, Y., Liu, M., and Zhang, L. (2017, January 25\u201330). Study on Path Planning of Ship Collision Avoidance in Restricted Water base on AFS Algorithm. Proceedings of the 27th International Ocean and Polar Engineering Conference, San Francisco, CA, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"294","DOI":"10.5391\/IJFIS.2017.17.4.294","article-title":"Study on the construction of stage discrimination model and consecutive waypoints generation method for ship\u2019s automatic avoiding action","volume":"17","author":"Gia","year":"2017","journal-title":"Int. J. Fuzzy Log. Intell. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lyu, H., and Yin, Y. (2018). COLREGS-constrained real-time path planning for autonomous ships using modified artificial potential fields. J. Navig., 1\u201321.","DOI":"10.1017\/S0373463318000796"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.eswa.2016.11.005","article-title":"A new deterministic approach in a decision support system for ship\u2019s trajectory planning","volume":"71","author":"Lazarowska","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Rocha, A.F. (1992). Neural Nets\u2014A Theory of Brain an Machines, Springer.","DOI":"10.1007\/3-540-55949-3"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/(SICI)1098-111X(199901)14:1<79::AID-INT6>3.0.CO;2-6","article-title":"Involving objective and subjective aspects in multistage decision making and control under fuzziness: dynamic programming and neural network","volume":"14","author":"Kacprzyk","year":"1999","journal-title":"Int. J. Intell. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Pedrycz, W., and Gomide, E. (2007). Fuzzy Systems Engineering Toward Human Centric Computing, Wiley.","DOI":"10.1002\/9780470168967"},{"key":"ref_22","unstructured":"Osborne, M.J. (2004). An Introduction to Game Theory, Oxford University Press."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"215","DOI":"10.4028\/www.scientific.net\/SSP.210.215","article-title":"Optimization-supported decision-making in the marine game environment","volume":"210","author":"Lisowski","year":"2014","journal-title":"Solid State Phenom."},{"key":"ref_24","unstructured":"Basar, T., and Olsder, G.J. (2013). Dynamic Non-Cooperative Game Theory, SIAM."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Nisan, N., Roughgarden, T., Tardos, E., and Vazirani, V.V. (2007). Algorithmic Game Theory, Cambridge University Press.","DOI":"10.1017\/CBO9780511800481"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Millington, I., and Funge, J. (2009). Artificial Intelligence for Games, Elsevier.","DOI":"10.1016\/B978-0-12-374731-0.00008-6"},{"key":"ref_27","unstructured":"Engwerda, J.C. (2005). LQ Dynamic Optimization and Differential Games, John Wiley and Sons."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/1\/82\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:23:33Z","timestamp":1760185413000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/1\/82"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,4]]},"references-count":27,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2019,1]]}},"alternative-id":["rs11010082"],"URL":"https:\/\/doi.org\/10.3390\/rs11010082","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,4]]}}}