基于RBF-BP神经网络的煤炭企业物资分类算法  

A material classification algorithm based on RBF-BP netural network in coal enterprises

作　　者：陈聪[1] 卢建军[1] 卫晨[2] 战金龙[1] 

机构地区：[1]西安邮电大学通信与信息工程学院,西安710121 [2]西安邮电大学管理工程学院,西安710121

出　　处：《桂林电子科技大学学报》2015年第5期366-370,共5页Journal of Guilin University of Electronic Technology

基　　金：陕西省自然科学基金(2011JM8027)

摘　　要：针对现有煤炭企业在物资管理中存在分类粗放、评价标准主观、计算规模大等问题,为提高煤炭企业中物资分类的效率,提出一种基于RBF-BP神经网络的煤炭企业物资分类算法。根据煤炭物资相关数据,建立算法预测模型,对煤炭物资分类进行预测。实验结果表明,RBF-BP神经网络算法较BP神经网络算法可提高煤炭企业物资分类的准确率,为煤炭企业物资的分类提供了较准确、可靠的方法。In view of extensive classification,subjective evaluation standard and large calculation existed in material management of coal enterprises,a material classification algorithm based on RBF-BP neural network is proposed to improve the efficiency of material classification in coal enterprises.According to the relevant data of coal material,the algorithm is established to forecast the coal material classification.The experimental results show that compared with BP neural network,RBF-BP neural network prediction can improve the correct rate of the coal enterprise＇s material classification,and provide a more accurate and reliable method for material classification in coal enterprises.

关 键 词：煤炭企业 RBF-BP神经网络 物资分类 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]