Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/7061
Title: Deterministic chaos model for self-organized adaptive networks in atmospheric flows
Authors: Selvan AMary 
Keywords: Earth Atmosphere--Theory;Systems Science and Cybernetics--Neural Nets, Adaptive Networks;Atmospheric Flows;Chaos Model;Fractal Geometry, Atmospheric Movements
Issue Date: 1989
Publisher: IEEE Proceedings of the National Aerospace and Electronics Conference
Publ by IEEE, Piscataway, NJ, United States
Project: Aerospace and Electronics Conference, 1989. NAECON 1989 
Dayton, OH 
22-26 May 1989 
Abstract: The complex spatiotemporal patterns of atmospheric flows resulting from the cooperative existence of fluctuations ranging in size from millimeters to thousands of kilometers are discussed. They are found to exhibit long-range spatial and temporal correlations. These correlations are manifested in the self-similar fractal geometry of the global cloud-cover pattern and in the inverse-power-law form of the atmospheric-eddy energy spectrum. Such long-range spatial and temporal correlations are ubiquitous in extended natural dynamical systems and are also a signature of the strange-attractor design characterizing deterministic chaos or self-organized criticality. The unified network of global atmospheric circulations is analogous to the neural network of the human brain.
URI: http://hdl.handle.net/123456789/7061
Appears in Collections:Conference or Workshop Item

Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.