Output details
15 - General Engineering
University of Liverpool
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Output 0 of 0 in the submission
Article title
A neural network approach for simulating stationary stochastic processes
Type
D - Journal article
Title of journal
Structural Engineering and Mechanics
Article number
-
Volume number
32
Issue number
1
First page of article
71
ISSN of journal
1225-4568
Year of publication
2009
URL
-
Number of additional authors
1
Additional information
In this paper neural networks are used directly for generating process records in Monte-Carlo simulation. The advantage is that the neural network extracts the random properties of the process directly from the data, so that an explicit estimation of a probability density function, associated with potential modelling errors, is unnecessary. The research was presented in a keynote paper at IEEE SSCI CIES 2013 (evidence file: Beer3-1) and a follow-on paper (evidence file: Beer3-2) won a best student prize at the same conference.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
