Summary
Due to their great impact on human life, Xevents require prediction. We discuss scenarios and recent results on predictions and the predictability of Xevents, focusing on nonlinear stochastic processes since they are assumed to provide the basis for extremes. These predictions are usually of a probabilistic nature, so the benefit of this type of uncertain prediction is an additional issue. As a specific example, we report on the prediction of turbulent wind gusts in surface wind.
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References
D. Sornette, this book
J.P. Crutchfield, D.P. Feldman, Regularities unseen, randomness observed: Levels of entropy convergence, Chaos 13, 25 (2003)
H.G. Schuster, Deterministic chaos, VCH Wiley (1997)
E.J. Gumbel, Statistics of extremes, Columbia University Press, New York (1958)
S. Coles, An introduction to statistical modeling of extreme values, Springer, Berlin Heidelberg New York (2004)
V.S. L’vov, A. Pomyalov, I. Procaccia, Outliers, extreme events, and multiscaling, Phys. Rev. E 63, 056118 (2001)
A. Bunde, J.F. Eichner, S. Havlin, J.W. Kantelhardt, The effect of long-term correlations on the return periods of rare events, Physica A 330, 1 (2003)
P. Gaspard, X.-J. Wang, Phys. Rep. 235, 291 (1993)
H. Kantz, T. Schreiber, Nonlinear time series analysis, 2nd edn, Cambridge University Press, Cambridge, UK (2004)
F. Takens, Detecting strange attractors in turbulence, Lecture Notes in Math. 898, Springer, Berlin Heidelberg New York (1981)
T. Sauer, J. Yorke, M. Casdagli, Embedology, J. Stat. Phys. 65, 579 (1991)
E.N. Lorenz, Atmospheric predictability as revealed by naturally occurring analogues J. Atmosph. Sci. 26, 636 (1969)
J.D. Farmer, J.J. Sidorowich, Predicting chaotic time series, Phys. Rev. Lett. 59, 845 (1987)
M. Ragwitz, H. Kantz, Markov models from data by simple nonlinear time series predictors in delay embedding spaces, Phys. Rev. E 65, 056201 (2002)
A.D. Sabin, Z. Sen, First-order Markov approach to wind speed modelling, J. Wind Eng. Ind. Aerodynam. 89, 262 (2001)
Main I. et al., Is the reliable prediction of individual earthquakes a scientific goal? Nature debates, 25 Feb. 1999 (see http://www.nature.com/nature/debates/earthquake/) (1999)
F. Paparella, A. Provenzale, L.A. Smith, C. Taricco, R. Vio, Local random analogue prediction of nonlinear processes, Phys. Rev. A 235, 233 (1997)
P. Grassberger, I. Procaccia, Characterization of strange attractors, Phys. Rev. Lett. 50, 346 (1983)
H. Kantz, D. Holstein, M. Ragwitz, N.K. Vitanov, Markov chain model for turbulent wind speed data, Physica A 342, 315 (2004)
J.A. Hanley, B.J. McNeil, The meaning and use of the area under the receiver operating characteristic (ROC) curve, Radiology 143, 29–36 (1982)
D. Sornette, Predictability of catastrophic events: Material, rupture, earthquakes, turbulence, financial crashes, and human birth, Proc. Natl. Acad. Sci. USA 99, 2522 (2002)
D. Lamper, S.D. Howison, N.F. Johnson, Predictability of large fluctuations in a competitive evolving population, Phys. Rev. Lett. 88, 017902 (2002)
N. Vandewalle, M. Ausloos, Ph. Boveroux, A. Minguet, How the financial crash of October 1997 could have been predicted, Eur. Phys. J. B 4, 139 (1998)
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© 2006 Center for Frontier Sciences
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Kantz, H., Altmann, E.G., Hallerberg, S., Holstein, D., Riegert, A. (2006). Dynamical Interpretation of Extreme Events: Predictability and Predictions. In: Albeverio, S., Jentsch, V., Kantz, H. (eds) Extreme Events in Nature and Society. The Frontiers Collection. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28611-X_4
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DOI: https://doi.org/10.1007/3-540-28611-X_4
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