首页> 外文会议>AICI 2010;International conference on artificial intelligence and computational intelligence >Prediction Interval on Spacecraft Telemetry Data Based on Modified Block Bootstrap Method
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Prediction Interval on Spacecraft Telemetry Data Based on Modified Block Bootstrap Method

机译:基于改进块自举法的航天器遥测数据预测间隔

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In spacecraft telemetry data prediction field, unknown residual distribution and great volatility of predicted value have hampered traditional prediction interval methods to follow forecast trend and give high-precision intervals. Hence, modified Block Bootstrap prediction interval Method is proposed in this paper. Contrast to traditional method, this method can enhance accuracy of non-stationary time series data prediction interval for its data sampling frequency can be adjusted by data character. In the end, an example is given to show the validity and practicality of this method.
机译:在航天器遥测数据预测领域,未知的残差分布和较大的预测值波动阻碍了传统的预测区间方法遵循预测趋势并给出高精度区间。因此,本文提出了一种改进的块自举预测间隔方法。与传统方法相比,该方法可以提高非平稳时间序列数据预测间隔的准确性,因为其数据采样频率可以通过数据特征进行调整。最后通过实例说明了该方法的有效性和实用性。

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