DocumentCode
2385733
Title
Modeling Dynamic Processes Using Granular Runge-Kutta Methods
Author
Co, Tomas
Author_Institution
Michigan Technol. Univ., Houghton
fYear
2007
fDate
2-4 Nov. 2007
Firstpage
55
Lastpage
55
Abstract
By incorporating the Runge-Kutta methods with functions defined within the frameworks of multilayered granular domains, a nonlinear continuous-time dynamic process can be efficiently modeled. The several layers allow for the construction of models spanning different granular size to be used for applications that require different levels of precision and efficiency. In this paper, we discuss a particular implementation of this approach using multilinear interpolation functions.
Keywords
Runge-Kutta methods; interpolation; neural nets; granular Runge-Kutta methods; multilayered granular domains; multilinear interpolation functions; Chemical engineering; Chemical technology; Computer networks; Eigenvalues and eigenfunctions; Fuzzy logic; Interpolation; Neural networks; Nonhomogeneous media; Steady-state; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location
Fremont, CA
Print_ISBN
978-0-7695-3032-1
Type
conf
DOI
10.1109/GrC.2007.100
Filename
4403066
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