Application research for prediction of time series data stream

Time series data stream contains a large amount of potential information that can be used as the basis for intelligent decision-making.It can provide an important support for the application of real-time decision by researching data stream prediction.Therefore,re-writable linked window technology is proposed that can replace the traditional sliding window technology,and combined with empirical mode decomposition and radial basis neural networks one online time series data stream prediction model is established called Online_DSPM.The experimental results indicate that the combined model has higher precision of prediction and better adaptability,compared with other single time series prediction models.