The present paper starts by presenting the two approaches, and compares them to identify their strong and weak points depending on the type of components constituting the system under consideration. These techniques have usually been considered until now as exclusive alternatives instead of synergistic tools. In many disciplines of ecology, System Dynamics and more recently Individual-Based modeling have emerged as the major tools to support this task. Taking a capsizing case as an example, the simulation results show that the novel TIP method minimizes the impact of search object motion on the search effectiveness and obtains higher POS values than those obtained by other methods.ĪbstractModeling could be summed up as the task of reproducing the structure and imitating the behavior of complex real-life systems with components interacting with one another at different scales. To evaluate the effectiveness of a search plan, an agent-based simulation environment of a maritime search mission is constructed based on the AnyLogic simulation platform. Then, the optimal search area is determined by an iterative search method starting from the cell with the highest probability of containment. The survivors' probable locations and mean drift direction are updated iteratively, while the probability map is developed by taking survivors' mean drift direction as a reference. To minimize the impact of search object motion, a time domain-based iterative planning (TIP) method is proposed in this article to obtain the optimal search areas. However, the search area is usually determined based on the survivors' probable locations at a given moment by existing planning methods, while the effects of the relative motion between the helicopter and the search objects are ignored, possibly leading to a significant decrease in the POS. ![]() To improve the probability of success (POS) of SAR missions, search areas should be carefully planned. ![]() Helicopters are widely used in maritime search and rescue (SAR) missions.
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