• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.603-608
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• 2014

In the maritime traffic environment, the near-miss between vessels is the situation approaching on collision course but collision accident is not occurred. In this study, in order to calculate the near-miss between navigating vessels, the discriminating equation using ship bumper theory and vessel position clustering methods are proposed. Applying proposed module to the vessel trajectories of the WANDO waterway, we assessment navigational risk factors of vessel type, navigational speed, meeting situation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.638-643
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• 2012

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.7
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• pp.775-782
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• 2017

The position of existing patrol ships has been decided according to subjective judgments, not purely by any reasonable or scientific criteria, because of a lack of access to marine accident positions. In this study, the optimal location of patrol ships is quantitatively determined based on historical marine accident data. The study area used included the coastal sea of Pohang in South Korea. In this study, a k-means clustering algorithm was used to derive the location of patrol ships, and then a Voronoi diagram was used to divide the region around each patrol ship. As a result, the average navigation distance for patrol ships was improved by 4.4 nautical miles, and the average arrival time was improved by 13.2 minutes per marine accident. Moreover, if the locations of patrol ships need to be changed flexibly, it will be possible to optimally arrange limited resources using the technique developed in this study to ensure a fast rescue.