Firstly, a coarse forecasting model based on only the primary influencing factor (that is the weight of iron in matte) is built using linear regression analysis, then, an error compensating model based on other influencing factors is built to improve the
Firstly, a coarse forecasting model based on only the primary influencing factor (that is the weight of iron in matte) is built using linear regression analysis, then, an error compensating model based on other influencing factors is built to improve the
首先应用线性回归技术建立了仅考虑主要影响因素（铜统含铁量）的粗略预报模型，而后，应用神经网络技术建立了考虑到多个次要影响因素的误差补偿模型，从而改进预报效果。