论文部分内容阅读
为解决区域火电行业NOx排放量的预测问题,在原始灰色模型基础上做出改进,提出了基于指数平滑的改进灰色模型,并将该模型与广义神经网络相结合,建立了基于改进灰色与广义神经网络的组合预测模型。以1998—2011年火电行业NOx排放量数据为基础,对提出的组合预测模型与灰色模型和广义神经网络模型的预测结果进行了对比。结果表明:建立的组合模型预测结果更为精准,能够更有效应用于区域火电行业NOx排放量的预测问题。
In order to solve the problem of predicting NOx emission in regional thermal power industry, an improved gray model based on the original gray model is proposed. An improved gray model based on exponential smoothing is proposed. Combining this model with generalized neural network, Neural Network Combination Forecasting Model. Based on the data of NOx emissions from the thermal power industry from 1998 to 2011, the proposed combination forecasting model is compared with that of the gray model and the generalized neural network model. The results show that the combined model is more accurate and can be more effectively used in the prediction of NOx emissions in the regional thermal power industry.