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Packard, Norman H. Meyer, Thomas Patrick 2011-05-07T13:44:16Z 2011-05-07T13:44:16Z 10000-01-01 1992 This thesis concerns the long range prediction of high dimensional chaotic systems. To this end, I investigate the important relationship between predictability and non-uniformity of information loss throughout the state space of a chaotic system. I introduce a genetic algorithm to build predictive models by exploiting this nonuniformity. The algorithm searches for the regions of state space which remain most predictable for a given time into the future. I use the algorithm to investigate the predictability of both model chaotic systems and physical data from a fluid flow experiment. Made available in DSpace on 2011-05-07T13:44:16Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9215856.pdf: 3404620 bytes, checksum: 10678d1b301d88f1da527b5ef8ae2353 (MD5) Previous issue date: 1992 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T14:58:33Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:27:32-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission ETDs are only available to UIUC Users without author permission U of I Only AAI9215856 (UMI)AAI9215856 http://hdl.handle.net/2142/22574 eng Copyright 1992 Meyer, Thomas Patrick Physics, General Long-range predictability of high-dimensional chaotic dynamics text Physics Physics University of Illinois at Urbana-Champaign Dissertation Ph.D.