基于协同过滤推荐的无人机与应急救援任务个性化匹配研究OA

Post-disaster matching of UAV models with emergency task characteristics is critical for enhanc-ing aviation rescue capabilities.However,in the era of rapid development of the"low-altitude economy",UAVs have demonstrated characteristics of diversified models,differentiated functions,and complementary perfor-mance,which significantly increases the difficulty of matching UAVs with rescue tasks.To address this chal-lenge,a precision matching method between UAVs and emergency rescue tasks is proposed based on their hetero-geneous characteristics.First,text mining methods are employed to establish feature attribute scales for both UAVs and rescue tasks.Second,a collaborative filtering recommendation algorithm is implemented to achieve accurate matching between UAVs and mission requirements.Finally,through the simulation of various rescue scenarios including casualty search and rescue,communication support,material delivery,and forest fire suppres-sion-typical post-disaster operations-the proposed method successfully identifies the top 5 most suitable UAV models for each scenario.The results validate the feasibility and effectiveness of our methodology while provid-ing actionable references for emergency management departments.This research contributes to optimized re-source allocation in disaster response operations and advances decision-making support systems for emergency aviation rescue.