<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>This paper presents an attempt to applying neural networks for assessment of parameters of standard manoeuvrability tests, i.e. circulation test and zig-zag test. Methodological approach to application of neural networks as well as applied network structures and neuron activation functions are generally presented. Also, results of simulations performed by means of the elaborated networks are given in comparison with test cases selected at random. In order to analyze and reveal general trends, correlation relationships between results from network simulations and test cases were calculated and are presented as well.</p></abstract>

This paper presents an attempt to applying neural networks for assessment of parameters of standard manoeuvrability tests, i.e. circulation test and zig-zag test. Methodological approach to application of neural networks as well as applied network structures and neuron activation functions are generally presented. Also, results of simulations performed by means of the elaborated networks are given in comparison with test cases selected at random. In order to analyze and reveal general trends, correlation relationships between results from network simulations and test cases were calculated and are presented as well.

Application of artificial neural networks to assessment of ship manoeuvrability qualities

Polish Maritime Research

This paper presents an attempt to applying neural networks for assessment of parameters of standard manoeuvrability tests, i.e. circulation test and zig-zag...

Application of artificial neural networks to assessment of ship manoeuvrability qualities

Online veröffentlicht: 23. Juli 2008

Seitenbereich: 15 - 21

DOI: https://doi.org/10.2478/v10012-007-0059-0

Schlüsselwörter
neural networks, ship manoeuvrability qualities

This content is open access.

Application of artificial neural networks to assessment of ship manoeuvrability qualities

Online veröffentlicht: 23. Juli 2008

Seitenbereich: 15 - 21

DOI: https://doi.org/10.2478/v10012-007-0059-0

Schlüsselwörterneural networks, ship manoeuvrability qualities

This content is open access.

Schlüsselwörter
neural networks, ship manoeuvrability qualities