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Telemetry data of flight task are multi-dimensional time-series data streams sequentially produced by subsystem, It reflects whether the function of each subsystem is normal, Accurate prediction is an important basis for research and judgment. Aiming at the disadvantage that the existing time series prediction algorithm will deteriorate over time, A dynamic weighted neural network integration algorithm based on ensemble learning principle is proposed. By means of Strong data fitting ability of neural network, generalization characteristic of The ensemble learning algorithm, has the and adaptability of the dynamic weighting algorithm for the drifting characteristic of data, The overall prediction accuracy of the algorithm is improved, Experiments show that this algorithm can improve the prediction accuracy remarkably， and Restrain data drift to some extent.