基于概率神经网络的煤炭企业物资分类方法研究

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,提出了基于概率神经网络的分类方法。该方法以物资较为通用的供求度、价值度和供应效率3个评价指标的量化样本数据作为输入数据,利用概率神经网络建立物资分类模型,并通过Matlab仿真出分类结果,实现了煤炭物资重要程度的科学分类。实际测试结果验证了该方法的科学性与准确性。

Research of classification method of materials and equipments of coal enterprise based on probabilistic neural network

In view of problems of extensive classification,subjective evaluation standard and large calculation existed in materials and equipments management of coal enterprises,a classification method based on probabilistic neural network was proposed.The method takes quantitative sample data of three evaluated indices of degree of supply and demand,degree of value and supply efficiency as input and uses probabilistic neural network to establish material classification model.It uses Matlab to simulate classification results and realizes scientific classification according to importance degree of coal materials and equipments.The actual test results show that the method is scientific and accurate.