Neural-network-based approximations for solving partial differential equations
β Scribed by Dissanayake, M. W. M. G. ;Phan-Thien, N.
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 312 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1069-8299
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
nonlinear evolution, and B is the M Ο« N dimensional noise term, which is a functional of , and multiplies an A robust semi-implicit central partial difference algorithm for the numerical solution of coupled stochastic parabolic partial differen-N dimensional real or complex Gaussian-distributed stot
## Abstract A Chebyshev expansion method for the parabolic and Burgers equations is developed. The spatial derivatives are approximated by the Chebyshev polynomials and the time derivative is treated by a finiteβdifference scheme. The accuracy of the resultant is modified by using suitable extrapol