𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Hierarchical Monte Carlo methods for fractal random fields

✍ Scribed by Frank W. Elliott; Andrew J. Majda; David J. Horntrop; Richard M. McLaughlin

Publisher
Springer
Year
1995
Tongue
English
Weight
723 KB
Volume
81
Category
Article
ISSN
0022-4715

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

A Fourier–Wavelet Monte Carlo Method for
A Fourier–Wavelet Monte Carlo Method for Fractal Random Fields
✍ Frank W. Elliott Jr.; David J. Horntrop; Andrew J. Majda πŸ“‚ Article πŸ“… 1997 πŸ› Elsevier Science 🌐 English βš– 598 KB

(1.1) A new hierarchical method for the Monte Carlo simulation of random fields called the Fourier-wavelet method is developed and where 0 Ο½ H Ο½ 1 is the Hurst exponent and Ν—ΠΈΝ˜ denotes applied to isotropic Gaussian random fields with power law spectral the expected value. ## density functions. Thi

A Monte Carlo method for simulating frac
A Monte Carlo method for simulating fractal surfaces
✍ Mingqing Zou; Boming Yu; Yongjin Feng; Peng Xu πŸ“‚ Article πŸ“… 2007 πŸ› Elsevier Science 🌐 English βš– 962 KB

A Monte Carlo method is presented for simulating rough surfaces with the fractal behavior. The simulation is based on power-law size distribution of asperity diameter and self-affine property of roughness on surfaces. A probability model based on random number for asperity sizes is developed to gene

Adaptive random search in Quasi-Monte Ca
Adaptive random search in Quasi-Monte Carlo methods for global optimization
✍ Guiyuan Lei πŸ“‚ Article πŸ“… 2002 πŸ› Elsevier Science 🌐 English βš– 569 KB

## Quasi-Monte Carlo random search is useful in nondifferentiable optimization. Borrowing ideas of population evolution from genetic algorithms, we introduce an adaptive random search in quasi-Monte Carlo methods (AQMC) for global optimization. Adaptive technique is used such that local search can