基于小波分析的导弹装备备件需求组合预测

Combination Forecasting of Missile Equipment Spare Parts Demand Based on Wavelet Analysis

针对导弹装备备件需求呈现非线性、非平稳的特征,提出了把小波分析理论应用于导弹装备备件需求预测的构想.首先根据总体评价指标来确定小波最佳分解级数,将备件需求时间序列分解到不同尺度上以减少原始序列的随机性和波动性;然后对具有平稳特性的高频信息用改进动态自适应隔代映射遗传算法和阻尼最小二乘法优化的ARMA模型进行预测,而对反映整体趋势的低频信息用GM(1,1)模型进行预测;再将各模型的预测结果进行叠加,从而得到原始序列的预测值.最后通过导弹装备备件需求的实例,验证了本方法的有有效性和可行性.

Due to the non-stability and non-linearity characteristic of missile equipment spare parts demand, the thought of wavelet analysis theory used on missile equipment spare parts demand forecasting. The best grading of its decomposition of wavelet was determined in terms of the collective evaluation index,and spare parts demand time series were decomposed into different scales in order to reduce the randomicity and volatility of original time series; The high frequency signals were forecasted with ARMA model optimized by the improved self-adaptive intergeneration projection genetic algorithm and damping least-squares method, and the low frequency was forecasted with GM（1,1） model;the respective forecast result were integrateA to get the forecast value of the original time series. Through an experiment of missile equipment spare parts demand, the feasibility and effectiveness of this method was oroven.