Name
Abstract | ||
|---|---|---|
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 fractional-order 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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.4304/jcp.9.2.322-327 | JOURNAL OF COMPUTERS |
Keywords | Field | DocType |
Fractional Order, Gray, Prediction, Taylor expansion | Pattern recognition,Computer science,Algorithm,Artificial intelligence,Taylor series,Gray (unit) | Journal |
Volume | Issue | ISSN |
9 | 2 | 1796-203X |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuran Liu | 1 | 2 | 1.87 |
| Mingliang Hou | 2 | 5 | 3.35 |