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

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.