CNS algorithms for temporal chaos -- CNS algorithms for spatio-temporal chaos -- On the origin of macroscopic randomness -- Ultra-chaos : a higher disorder than normal-chaos -- Numerical simulation of turbulence : true or false?
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SUMMARY OR ABSTRACT
Text of Note
"This book proposes a new strategy to gain "clean" reliable numerical simulations of chaos and turbulence, namely the Clean Numerical Simulation (CNS), which can greatly reduce numerical noises to a tiny level much smaller than that of true solutions so that numerical noises are negligible, and the corresponding numerical simulation is "clean" and thus reliable. By means of the CNS, one can gain "clean" reliable numerical simulations of chaotic systems in a long enough interval of time. The CNS provides a much more reliable tool than ever to study chaotic and turbulent systems in various fields of science and engineering. In this book, the author will describe the basic ideas of the CNS and illustrate the CNS as a new powerful tool for chaos and turbulence. Unlike traditional algorithms in single/double precision, the CNS can provide us the "clean" results of chaos and turbulence. Using these "clean" results as benchmark solutions, we can investigate many important scientific problems, such as the origin of macroscopic randomness, the influence of micro-level uncertainty and tiny external noises to chaos and turbulence, and so on. Comparing the "clean" CNS results with those badly "polluted" by numerical noises, one can investigate the influence of database noises on machine learning. Through this application and more, the author illustrates the validity and potential of the CNS. The CNS is as a new, powerful tool for chaos and turbulence. It opens a new door for us to enter a "clean" numerical world"--
TYPE OF ELECTRONIC RESOURCE NOTE
Text of Note
PDF file.
TOPICAL NAME USED AS SUBJECT
Entry Element
Chaotic behavior in systems
Entry Element
Dynamics
Entry Element
Nonlinear theories
Topical Subdivision
Mathematical models.
Topical Subdivision
Mathematical models.
Topical Subdivision
Mathematical models.
DEWEY DECIMAL CLASSIFICATION
Edition
23/eng/20231005
PERSONAL NAME - PRIMARY RESPONSIBILITY
Entry Element
Liao, Shijun,
Dates
1963-
Relator Code
Author
ORIGINATING SOURCE
Country
Iran
Agency
University of Tehran. Library of College of Science