Abstract
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.
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Luan, J., Tang, J., Lu, C. (2010). Prediction Interval on Spacecraft Telemetry Data Based on Modified Block Bootstrap Method. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16527-6_6
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DOI: https://doi.org/10.1007/978-3-642-16527-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16526-9
Online ISBN: 978-3-642-16527-6
eBook Packages: Computer ScienceComputer Science (R0)