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With the development of the maritime economy, sea traffic is becoming more and more crowded, and sea accidents are also increasing. Research on maritime search and rescue decision-making technology cannot be delayed. This paper studies the maritime search and rescue decision algorithm, based on the optimal search theory. It also analyzes three important concepts: Probability of containment (POC), probability of detection (POD), and probability of success (POS) involved in the maritime search and rescue decision-making process. In this paper, the calculation methods of POC and POD variables have been improved, and the search success rate has been improved to some extent. Finally, an example analysis of the maritime search and rescue incident is given. Through verification, the algorithm proposed in this paper can support maritime search and rescue decisions.
Donatien Agbissoh Otote; Benshuai Li; Bo Ai; Song Gao; Jing Xu; Xiaoying Chen; Guannan Lv. A Decision-Making Algorithm for Maritime Search and Rescue Plan. Sustainability 2019, 11, 2084 .
AMA StyleDonatien Agbissoh Otote, Benshuai Li, Bo Ai, Song Gao, Jing Xu, Xiaoying Chen, Guannan Lv. A Decision-Making Algorithm for Maritime Search and Rescue Plan. Sustainability. 2019; 11 (7):2084.
Chicago/Turabian StyleDonatien Agbissoh Otote; Benshuai Li; Bo Ai; Song Gao; Jing Xu; Xiaoying Chen; Guannan Lv. 2019. "A Decision-Making Algorithm for Maritime Search and Rescue Plan." Sustainability 11, no. 7: 2084.
This paper presents three design techniques to optimize dynamic maps for cognitive efficiency. An interactive time legend, which has functions such as play, pause, stop and speed control, can help users to remember, identify and understand the dynamic phenomena in dynamic maps by expressing time information. And a user-defined data filter can help users to reduce the amount of dynamic map information and focus on the phenomena they are interested in. Spatiao-temporal data aggregation can compress the amount of dataset to establish a dynamic map of appropriate time resolution. It can also display the same dataset using different temporal units, such as from year to composite month or composite week, to find the hidden meaningful patterns.
Wenpeng Xin; Bo Ai; Zhen Wen; Agbissoh Donatien Otote. Cognitive Optimization Techniques of Spatiao-Temporal Dynamic Map. Journal of Physics: Conference Series 2018, 1087, 062050 .
AMA StyleWenpeng Xin, Bo Ai, Zhen Wen, Agbissoh Donatien Otote. Cognitive Optimization Techniques of Spatiao-Temporal Dynamic Map. Journal of Physics: Conference Series. 2018; 1087 (6):062050.
Chicago/Turabian StyleWenpeng Xin; Bo Ai; Zhen Wen; Agbissoh Donatien Otote. 2018. "Cognitive Optimization Techniques of Spatiao-Temporal Dynamic Map." Journal of Physics: Conference Series 1087, no. 6: 062050.