In order to improve the prediction accuracy of iron ore consumption, using a time series forecasting method based on intelligent calculation.
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。
Moving average method is one of time series forecasting method, if time series have no apparent tendency moving, using moving average method can accurately reflect actual situation.
移动平均法是一种时间序列预测法，当时间序列没有明显的趋势变动时，使用移动平均就能够准确地反映实际情况。
In the final chapter, we mine stock trading data using time series method, find out the model and outliers in the data and, at last, we show the more exact forecasting model and outlier mining method.
第五章利用时间序列的方法对证券交易数据进行了挖掘，找出了数据中的模式和异常，相对传统方法而言，给出了更精确的预测模型和异常挖掘方法。
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