基于BP神经网络的战时维修器材供应商评价方法研究  

Research on the Evaluation Method of Maintenance Equipment Suppliers Based on BP Neural Network

作　　者：马飒飒 宋明昌 孙晶 MA Sasa;SONG Mingchang;SUN Jing(Unit 32181 of PLA,Xi'an Shaanxi 710032)

机构地区：[1]中国人民解放军32181部队,陕西西安710032

出　　处：《软件》2024年第12期10-13,共4页Software

基　　金：军队计划科研项目(LY2023ZW037)。

摘　　要：针对传统战时维修器材供应商评价方法中因主观因素影响较大、存在冗余指标等情况,而导致供应商评价分类效果不佳的问题,提出基于BP神经网络的战时维修器材供应商评价方法。设计了基于BP神经网络的战时维修器材供应商评价模型,并通过15家供应商的数据进行了模型验证。实验数据显示,该方法可以明显提升战时维修器材供应商评价时的分类预测效果,为战时维修器材供应商选择以及战时维修器材供应链管理的快速构建和高效运作提供可靠依据。Aiming at the problem of poor supplier evaluation and classification performance due to subjective factors and redundant indicators in the selection of wartime maintenance equipment suppliers,a classification method for wartime maintenance equipment supplier selection based on BP neural network is proposed.A wartime maintenance equipment supplier selection model based on BP neural network was designed,and the model was validated using data from 15 suppliers.Experimental data shows that this method can significantly improve the classification prediction performance when selecting wartime maintenance equipment suppliers,providing reliable basis for the rapid construction and efficient operation of wartime maintenance equipment supplier selection and supply chain management.

关 键 词：BP神经网络 战时 维修器材 供应商评价 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]