战中物资需求预测及布谷鸟指数平滑算法

Materials Forecasting in Middle-war Based on Cuckoo Exponential Smoothing Algorithm

针对传统战前物资预测存在的问题和不足,立足于战役发生过程中的实时数据,运用元后发式算法(布谷鸟搜索算法)并结合指数平滑算法,设计了战中物资预测的布谷鸟指数平滑算法。利用实例数据对所设计的算法进行收敛分析、精度分析、算法对比分析等性能试验,结果表明:所设计的布谷鸟指数平滑算法具有计算时间短、收敛精度高等优点;能够配合传统战前物资预测方法,依据战役发生过程中的实时数据,对物资消耗、需求进行战中短期、实时预测,补充、完善、拓展了战时物资预测理论。

Contraposing the problem and deficiency of traditional pre-war materials prediction, and based on real-time data oncampaign, the middle- war materials forecasting algorithm：cuckoo search exponential smoothing algorithm is designed. Combinedwith battle scenario data, convergence analysis, accuracy analysis, algorithm comparative analysis are conducted. The results showthat, cuckoo exponential smoothing algorithm has small error and high precision, with time short features. It is able to cope with thetraditional pre-war materials prediction measure to forecasting middle-war materials in real-time and short term. It supplements, im-proves and expands the wartime prediction theory.