中文摘要：

针对低空应急救援过程中救援物资需求的多样性与不确定性,提出基于反馈补偿K-means相似搜索的物资需求预测算法。通过比较非平稳数据处理方法,采用差分自回归平均移动模型（ARIMA）对历史灾情数据进行平滑处理;将预处理后的灾情数据运用基于反馈补偿的K-means方法进行聚类分析;再对比夹角余弦,杰卡德相似系数以及相关系数这3种方法,搜索出相似度最大历史灾情案例,并线性求解当前低空应急救援所需物资量。实验结果表明,在基于反馈补偿K-means相似搜索的物资需求预测过程中,运用相关系数搜索的误差是最小的,方法不仅提高了大数据处理能力,而且在一定程度上提高了预测精度。

英文摘要：

Aiming at sloving the diversity and uncertainty of the supplies demand in the process of aviation rescue, a prediction algorithm based on feedback compensation K- means similar search is proposed. First, smoothing the historical disaster data through ARIMA model; then, making a cluster analysis on the pretreated disaster data through feedback compensation K- means algorithm; finally, searching out the most similar case in historical disaster data by using correlation coefficient, and obtaining the current sup- plies demand for aviation rescue through linear contrast. A mass of real seismic data was conducted to ver- ify the validity of the method, and the experimental results show that the forecasting method based on feedback compensation K- means can not only improves the ability of data processing, but also improves the accuracy of prediction.