Particle swarm optimization-based collision avoidance
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Erişim
info:eu-repo/semantics/openAccessAttribution-NonCommercial 3.0 United Stateshttp://creativecommons.org/licenses/by-nc/3.0/us/Tarih
2019Üst veri
Tüm öğe kaydını gösterKünye
Inan, T., & Baba, A. F. (2019). Particle swarm optimization-based collision avoidance. Turkish Journal of Electrical Engineering and Computer Sciences, 27(3), 2137-2155. doi:10.3906/elk-1808-63Özet
Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy logic system to obtain the risk of collision, and a particle swarm optimization algorithm to find the safe and shortest path for collision avoidance.
Kaynak
Turkish Journal of Electrical Engineering and Computer SciencesCilt
27Sayı
3Koleksiyonlar
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