基于组合模型的矿山设备产量预测研究

鉴于矿山设备产量具有灰色和不确定性的特征，本文利用矿山设备产量的历史数据，建立了基于灰色和BP神经网络的组合预测模型。组合预测模型中各单一模型的权系数通过熵值法确定，克服了传统权系数确定方法的主观性，使得组合预测方法更具客观性最后，实例验证了所构建的组合模型较传统的单一预测模型有良好的预测效果。

Study to the System for Forecasting the Yield of Mineral Equipment Based on Combined Model

For the yield of mineral equipment possesses the characteristic of grey and uncertainty, the historical data about the yield of mineral equipment was applied to establish the combined forecasting model based on grey and BP neural network.. The weight coefficient of each model in the combined forecasting model were determined by entropy algorithm, thus the subjectivity of traditional weight coefficient determination approach is overcame, the combined forecast approach is more subjective. Finally, that the combined model has more forecasting effect than the traditional single forecasting model was validated by example.