Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

An efficient Monte Carlo simulation strategy based on model order reduction and artificial neural networks

An efficient Monte Carlo simulation strategy based on model order reduction and artificial neural... In this paper, we present a new approach that enables the Monte Carlo simulation of complex nonlinear systems with considerably less computational effort compared to the classical Monte Carlo simulation. Hereby, we propose a combination of the proper orthogonal decomposition and neural networks. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings in Applied Mathematics & Mechanics Wiley

An efficient Monte Carlo simulation strategy based on model order reduction and artificial neural networks

Loading next page...
1
 
/lp/wiley/an-efficient-monte-carlo-simulation-strategy-based-on-model-order-RNm7L7IQs7

References (9)

Publisher
Wiley
Copyright
Copyright © 2017 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1617-7061
eISSN
1617-7061
DOI
10.1002/pamm.201710113
Publisher site
See Article on Publisher Site

Abstract

In this paper, we present a new approach that enables the Monte Carlo simulation of complex nonlinear systems with considerably less computational effort compared to the classical Monte Carlo simulation. Hereby, we propose a combination of the proper orthogonal decomposition and neural networks. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Journal

Proceedings in Applied Mathematics & MechanicsWiley

Published: Dec 1, 2017

There are no references for this article.