基于智能计算的铁矿石消费预测

为了提高铁矿石消费量的预测精度，采用一种基于智能计算的时间序列预测方法。该方法首先对粒子群算法进行改进，然后利用它的全局寻优能力优化RBF神经网络的关键参数，最后了建立铁矿石的消费预测模型。实验结果表明：与其他预测方法相比，该方法预测精度较高，为铁矿石消费预测提供了一种新途径。

Consumption Prediction of Iron Ore Based on Intelligent Calculation

In order to improve the prediction accuracy of iron ore consumption，using a time series forecasting method based on intelligent calculation.First，the particle swarm algorithm was improved，and it was used to optimize the ability of global optimization of key parameters of RBF neural network；finally iron ore consumption prediction model was established.The results showed that: this method hada high prediction accuracy compare with other prediction methods，and providesda new way for iron ore consumption forecast.