智能系统学报2025，Vol.20Issue(2)：495-505,11.DOI:10.11992/tis.202402014
一种基于灰色理论和弱缓冲算子的装备备件预测方法
A prediction method for equipment spare parts based on grey theory and weak buffering operator
摘要
Abstract
Spare parts shortage or redundancy is a common issue in maintenance assurance tasks,which seriously af-fects efficiency.How to make accurate and effective spare parts prediction has become crucial in maintenance support.Due to the short-term and irregular nature of spare part prediction,gray prediction has become a commonly used meth-od,but the current gray prediction still has the problem of insufficient accuracy.To enhance the accuracy,gray models and methods are improved by smoothing the original sequence and refining the model,four different models and three smoothing functions are selected,and a new weak buffer operator is further constructed to reduce the error due to the cu-mulative calculation.The experiments show that under different models and smoothing functions,the constructed oper-ators are feasible to improve the accuracy,and the improvement effect is obvious,and more accurate results can be ob-tained by combining with model improvement and smoothing.关键词
备件预测/灰色模型/光滑度/模型改进/缓冲算子/维修保障/资源预测/预测精度Key words
spare part prediction/gray model/smoothness/model improvement/buffer operator/maintenance assur-ance/resource prediction/prediction accuracy分类
信息技术与安全科学引用本文复制引用
齐小刚,姚兆冬..一种基于灰色理论和弱缓冲算子的装备备件预测方法[J].智能系统学报,2025,20(2):495-505,11.基金项目
国家自然科学基金项目(62373291,62372354). （62373291,62372354）
