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Modeling of point search area and rescue path for maritime air crash

机译:海上空难点搜索区域和救援路径建模

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Point search nearby sea level is a crucial step in search and rescue works, which is very important for air crash search in recent years. Modeling of point search area and rescue path for maritime air crash is proposed, where the minimum wreckage floating zone is obtained by probability density distribution and we divide it into regular hexagon based on Honeycomb Model to identify the point search area that is endowed with priority by Bayesian Formula. In experiments, we assume some spots in the map which can find debris in ocean, and a point search route is obtained by using annealing algorithm and Genetic algorithm, which strips out 5% in time compared with the current strategy. Using point search nearby sea level, it would be fast and efficient for different kinds of search and rescue fields, mining, water searching on Mars and so on.
机译:在海平面附近进行点搜索是搜索和救援工作中的关键步骤,这对于近年来的空难搜索非常重要。提出了海上空难的点搜索区域和救援路径的建模方法,通过概率密度分布得到最小残骸漂浮区,并基于蜂窝模型将其划分为正六边形,从而确定了优先赋予的点搜索区域贝叶斯公式。在实验中,我们假设地图上的某些点可以找到海洋中的碎片,并且通过使用退火算法和遗传算法获得了点搜索路线,与当前策略相比,该方法在时间上节省了5%。使用附近海平面的点搜索,对于不同种类的搜救场,采矿,火星上的水搜索等,它将快速有效。

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