Fractional Order Relative Correlation Algorithm of Uncertain Time Sequence

Hou, Mengshu; Liu, Yuran; Fu, Yanglie

doi:10.1109/iccis.2012.160

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Cited by 2 publications

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“…These two concepts can be compared to the difference of a photo and a video [5][6][7][8]. Fractional order can better describe gray information and achieve a more accurate forecast [9][10][11][12][13][14][15][16][17][18].…”

Section: A Algorithm Thoughtmentioning

confidence: 99%

Liu-hou Prediction Algorithm for Weak Source Uncertainty Information

Liu¹,

Hou²

2014

JCP

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This paper proposed the fractional order gray prediction algorithm to improve prediction accuracy in uncertainty signal. This paper is the first to propose the measurement method of the gray information of signals. The fractional order gray prediction algorithm is deduced through fractional order Taylor expansion formula. The measurement method of the gray information of signals is provided by analyzing the relations between fractionalorder differential orders and prediction accuracy. Fractional order gray prediction algorithm spares the complex operation of whitening gray information and utilizes gray information. Experiments show that the prediction accuracy of fractional order gray prediction algorithm was significantly increased compared with the GM (1, 1) algorithm.

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