CAJ | 학술논문

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。
침대현유매탄기업재물자관리중존재분류조방、평개표준주관、계산규모대등문제,위제고매탄기업중물자분류적효솔,제출일충기우 RBF-BP 신경망락적매탄기업물자분류산법。근거매탄물자상관수거,건립산법예측모형,대매탄물자분류진행예측。실험결과표명,RBF-BP 신경망락산법교 BP 신경망락산법가제고매탄기업물자분류적준학솔,위매탄기업물자적분류제공료교준학、가고적방법。
In view of extensive classification,subjective evaluation standard and large calculation existed in material manage-ment of coal enterprises,a material classification algorithm based on RBF-BP neural network is proposed to improve the effi-ciency of material classification in coal enterprises.According to the relevant data of coal material,the algorithm is estab-lished 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.