基于遗传优化灰色神经网络的吨煤生产成本预测研究  

Grey Neural Network Based on Genetic Optimization Tons of Coal Production Cost Prediction

作　　者：宁贝贝[1] 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9期1569-1572,1643,共5页Computer & Digital Engineering

摘　　要：在煤炭企业实际生产中,影响煤生产成本的因素非常复杂,为了对煤的生产成本进行合理预测,论文提出了基于遗传优化灰色神经网络的方法对吨煤生产成本进行研究。通过Matlab仿真,将原始数据与预测数据的拟合程度相比较,确定了此预测方法的科学性与准确性,为最终的煤炭生产成本的控制提供了可靠的依据。The influencing factors of coal production cost is very complex in the coal enterprise practical production. In order to reasonably predict the production cost of coal, the grey neural network optimization method based on the genetic study of tons of coal production cost is put forward in this paper. Through Matlab simulation, the original data and forecas- ting data, in comparison with the fitting degree of determine the scientific and the accuracy of the prediction method, provides a reliable basis for the final coal production cost control.

关 键 词：煤炭企业 吨煤生产成本 遗传优化灰色神经网络 预测 

分 类 号：TP312[自动化与计算机技术—计算机软件与理论]