An Adaptive Forecasting Method for Time-Series Data Streams
时间序列数据流的自适应预测

An adaptive forecasting method that combines the merits of the precision of artificial intelligence forecasting method and the rapidness of times-series forecasting method, called AFStreams, is proposed. It can estimate the forecasting-step self adaptively from the change ratio of stream-values and can generate proved optimal track of forecasting points with the minimum computation cost from limited resources. Experiments proved that AFStreams can adapt to the changes of data well and provide tradeoff between computing complexity and forecasting precision.