基于BP神经网络的设备维修人员训练数量预测方法研究  

Device Maintenance Training Personnel Prediction Based on BP Neural Network

作　　者：李锋[1,2] 田霞[2] 宋文渊[2] 

机构地区：[1]军械工程学院科研部,石家庄050003 [2]军械工程学院设备指挥与管理系,石家庄050003

出　　处：《计算机与数字工程》2017年第7期1273-1277,共5页Computer & Digital Engineering

摘　　要：当前对于设备精确化保障的要求越来越高,如何科学准确地预测维修人员训练数量,是开展后续培训工作的重要基础。针对这一迫切需要,首先分析了影响设备维修人员训练数量的主要因素,然后探讨了BP神经网络在训练人员数量预测方面的适用性和基本原理,在此基础上利用BP神经网络构建了设备维修人员数量预测模型,并结合实例进行了验证应用,从而为制订维修人员训练计划提供方法支撑和参考依据。Currently, the requirements for device maintenance support are becoming more and more complex,and the accu-rate prediction of device maintenance training personnel is of fundamental for training plan and implementation. Aiming at the ur-gent requirement above, the main factors of maintenance training personnel are analyzed. Then, the applicability and theory of BP neural network for raining personnel prediction are discussed, and the maintenance training personnel model based on BP neural network is established. Finally, an example is presented to illustrate the model.

关 键 词：维修人员训练 BP神经网络 预测方法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]