基于邻域粗糙集和神经网络的缺材数据分析  

Analysis and Research on Shortage Data of Aviation Material Based on Neighborhood Rough Set and Neural Network

作　　者：任宇轩 徐常凯[2] REN Yuxuan;XU Changkai(Postgraduate Brigade,Air Force Logistics College,Xuzhou 221000,China;Department of Air Material and Four Station,Air Force Logistics College,Xuzhou 221000,China)

机构地区：[1]空军勤务学院研究生大队,江苏徐州221000 [2]空军勤务学院航材四站系,江苏徐州221000

出　　处：《火力与指挥控制》2022年第6期132-138,共7页Fire Control & Command Control

摘　　要：为解决空军航材保障工作中的短板问题,避免由于个别器材缺材致使飞机停飞,个别环节受阻导致任务受影响的情况发生,提出一种基于邻域粗糙集优化的神经网络对缺材停飞数据分析的方法,分析保障流程建立基于多维度属性体系的缺材停飞数据集,针对其混合型数据的特点,进行了算法的优化。通过验证,该方法可以得到最优决策属性集,预估缺材停飞的发生,加强了航材保障工作的提前性与科学性。In order to solve the shortcomings of the Air Force’s aviation material support work,and to avoid the situation that the aircraft is grounded due to the lack of material of individual equipment,and the obstruction of individual links which may affect the mission execution,an analysis method of grounded data for lacking of aviation material based on neighborhood rough set optimized neural network is proposed.The support process is analyzed and the grounded data set for lacking of aviation material based on multi-dimensional attribute system is established,and the algorithm is optimized according to the characteristics of the mixed data.Through verification,this method can obtain the optimal decision attribute set,and can predict the occurrence of grounding,due to lack of material and the advancement and scientific nature of aviation material support are strengthened.

关 键 词：航材 混合属性 属性约简 邻域粗糙集 神经网络 

分 类 号：V267[航空宇航科学与技术—航空宇航制造工程] E926[军事—军事装备学]