Constructing Runge–Kutta methods with the use of artificial neural networks
✍ Scribed by Anastassi, Angelos A.
- Book ID
- 121624729
- Publisher
- Springer-Verlag
- Year
- 2013
- Tongue
- English
- Weight
- 483 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0941-0643
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📜 SIMILAR VOLUMES
We give an overview of the construction of algebraic conditions for determining the order of Runge-Kutta methods and describe a novel extension for numerically solving systems of differential equations. The new schemes, called Elementary Differential Runge-Kutta methods, include as a subset Runge-Ku
For implicit Runge-Kutta methods intended for stiff ODEs or DAEs, it is often difficult to embed a local error estimating method which gives realistic error estimates for stiff/algebraic components. If the embedded method's stability function is unbounded at z = o0, stiff error components are grossl