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Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures
Joint Authors
Høgsberg, Jan
Voie, Per Erlend Torbergsen
Winther, Ole
Christiansen, Niels H.
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-02
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Training of an artificial neural network (ANN) adjusts the internal weights of the network in order to minimize a predefined error measure.
This error measure is given by an error function.
Several different error functions are suggested in the literature.
However, the far most common measure for regression is the mean square error.
This paper looks into the possibility of improving the performance of neural networks by selecting or defining error functions that are tailor-made for a specific objective.
A neural network trained to simulate tension forces in an anchor chain on a floating offshore platform is designed and tested.
The purpose of setting up the network is to reduce calculation time in a fatigue life analysis.
Therefore, the networks trained on different error functions are compared with respect to accuracy of rain flow counts of stress cycles over a number of time series simulations.
It is shown that adjusting the error function to perform significantly better on a specific problem is possible.
On the other hand.
it is also shown that weighted error functions actually can impair the performance of an ANN.
American Psychological Association (APA)
Christiansen, Niels H.& Voie, Per Erlend Torbergsen& Winther, Ole& Høgsberg, Jan. 2014. Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-496561
Modern Language Association (MLA)
Christiansen, Niels H.…[et al.]. Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. Journal of Applied Mathematics No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-496561
American Medical Association (AMA)
Christiansen, Niels H.& Voie, Per Erlend Torbergsen& Winther, Ole& Høgsberg, Jan. Comparison of Neural Network Error Measures for Simulation of Slender Marine Structures. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-496561
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496561