基于任务的装备器材非稳态需求预测

doi:10.3969/j.issn.1001-506X.2019.12.18

系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (12): 2796-2801.doi: 10.3969/j.issn.1001-506X.2019.12.18

基于任务的装备器材非稳态需求预测

杨帆1, 王铁宁1, 吴龙涛2, 于双双3

1. 陆军装甲兵学院装备保障与再制造系, 北京 100072;
2. 军事科学院防化研究院, 北京 102205; 3. 中国人民解放军96631部队, 北京 102206

出版日期:2019-11-25 发布日期:2019-11-26

Unstable equipment material demand forecasting based on tasks

YANG Fan1, WANG Tiening1, WU Longtao2, YU Shuangshuang3

1. Equipment Support and Remanufacturing Department, Army Academy of Armored Forces, Beijing 100072, China; 2. Research Institute of Chemical Defense, Academy of Military Science, Beijing 102205, China; 3. Unit 96631 of the PLA, Beijing 102206, China

Online:2019-11-25 Published:2019-11-26

摘要/Abstract

摘要：

基于任务的装备器材具有非稳态、小样本等特征,针对其需求难以准确预测的问题,提出非稳态区间划分和支持向量回归(support vector regression, SVR)的预测方法。首先根据非稳态度量函数将需求序列划分为稳态子区间,然后对各子区间采用SVR进行预测,同时针对基于径向基函数(radial basis function, RBF)核函数的SVR对参数的敏感性问题,采用布谷鸟搜索算法(cuckoo search, CS)对SVR参数进行寻优,最后将各区间的预测结果进行加权求和得到最终预测结果。算例对比分析表明,该方法能够一定程度上降低数据非稳态影响,提高任务器材需求预测准确率。

关键词: 任务器材, 非稳态, 需求预测, 支持向量回归

Abstract:

An unstable interval partition and support vector regression (SVR) method is proposed to solve small sample and unsteady demand prediction problem of equipment material based on tasks. First, the sequence of demand is decomposed into steady-state subintervals according to the measurement function. Then, SVR is carried out for each subinterval’s forecasting, and cuckoo search (CS) algorithm is used to optimize the radial basis function (RBF)-SVR kernel function parameters to solve its sensitivity problem. Finally, take weighted sum results of subintervals as the final forecasting result. The example shows that the proposed model can reduce the influence of unsteady state and improve the accuracy of task equipment materials prediction.

Key words: task materials, unsteady state, demand forecasting, support vector regression (SVR)

杨帆, 王铁宁, 吴龙涛, 于双双. 基于任务的装备器材非稳态需求预测[J]. 系统工程与电子技术, 2019, 41(12): 2796-2801.

YANG Fan, WANG Tiening, WU Longtao, YU Shuangshuang. Unstable equipment material demand forecasting based on tasks[J]. Systems Engineering and Electronics, 2019, 41(12): 2796-2801.

基于任务的装备器材非稳态需求预测

Unstable equipment material demand forecasting based on tasks

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