基于广义回归神经网络的煤炭企业成本预测  

Prediction of Coal Enterprise Cost Based on Generalized Tegression Neural Network

作　　者：孙方元 卫晨[2] 

机构地区：[1]西安邮电大学通信与信息工程学院,西安710061 [2]西安邮电大学管理工程学院,西安710061

出　　处：《计算机与数字工程》2015年第8期1378-1381,1551,共5页Computer & Digital Engineering

摘　　要：针对煤炭企业成本预测相关因素的复杂性,为了解决传统成本预测方法在煤炭企业成本预测问题上的不适用性和不准确性,提出了基于广义回归神经网络的煤炭企业成本预测方法。该方法基于广义回归神经网络算法,以物资消耗成本为例,以比较关键的八个影响因素标准化样本数据作为输入数据,构建了网络模型,并通过Matlab仿真出预测结果。结果表明该成本预测方法的科学性与准确性。The relative factors about the prediction of the coal enterprise cost are complex. The research of the predic- tion method of coal enterprise cost based on generalized regression neural network is proposed in this paper, in order to solve the inapplicability and inaccuracy of traditional cost prediction method in the coal enterprise. A network model has been built through generalized regression neural network, in the case of material cost and the eight key affecting factors of the standard- ization sample data as input data. Meanwhile, the results are predicted by Matlab simulation. It shows that the cost predic- tion method is scientific and accurate.

关 键 词：煤炭企业 成本预测 广义回归神经网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]