Abstract
Computation of ship maneuverability using ANN is based on ANN's nonlinear mapping function to perform the project from ship particular space to ship maneuverability space. It is more flexible to some extent to select input particulars and convenient to be used in ship design. BP(Back Propagation) networks and the neuron function are used in this paper. The learning algorithm is gradient descending combined with momentum factor. The sample data were condensed to 0. 1-0. 9 in advance. According to the result of 9 various ships' computation, the RMS is 0. 6137. Furthermore, 9 bulk ships are selected for ship's maneuverability prediction. After 12, 000 times training based on data of turning test of 8 bulk ships, the relative prediction precision of turning test of the 9th bulk ship is - 7. 16% (advance), 7. 16 % (transfer) and 0. 03% (tactical diameter).
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
