Publication Details |
| Category | Text Publication |
| Reference Category | Book chapters |
| DOI | 10.1007/978-3-7091-6230-9_117 |
| Title (Primary) | Application of the surrogate test to detect dynamic non-linearity in ground-level ozone time-series from Berlin |
| Title (Secondary) | Artificial neural nets and genetic algorithms. Proceedings of the International Conference in Prague, Czech Republic, 2001 |
| Author | Schlink, U.
; Haase, P. |
| Publisher | Kůrková, V.; Steele, N.C.; Neruda, R.; Kárný, M. |
| Source Titel | Springer Computer Science |
| Year | 2001 |
| Department | EXPOEPID |
| Page From | 469 |
| Page To | 472 |
| Language | englisch |
| Abstract | Recent applications of non-parametric methods to forecast ground level ozone concentrations are based on dynamic non-linearity of the data series. We explain the surrogate method to test this assumption, illustrate the method with non-linear data generated by the Lorenz system, and discuss our test results for Berlin ozone time-series. We find that the null-hypothesis of linearity is clearly rejected for 12- and 24-step-ahead predictions of hourly ozone concentrations. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=6774 |
| Schlink, U., Haase, P. (2001): Application of the surrogate test to detect dynamic non-linearity in ground-level ozone time-series from Berlin In: Kůrková, V., Steele, N.C., Neruda, R., Kárný, M. (eds.) Artificial neural nets and genetic algorithms. Proceedings of the International Conference in Prague, Czech Republic, 2001 Springer Computer Science Springer, Wien, New York, p. 469 - 472 10.1007/978-3-7091-6230-9_117 |
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