Title :
Modeling Dynamic Processes Using Granular Runge-Kutta Methods
Author_Institution :
Michigan Technol. Univ., Houghton
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;
Conference_Titel :
Granular Computing, 2007. GRC 2007. IEEE International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3032-1
DOI :
10.1109/GrC.2007.100
