ON THE USE OF NEURAL NETWORK TECHNIQUES FOR THE IDENTIFICATION OF SHIP STABILITY PARAMETERS AT SEA

In this paper, neural network techniques are used to identify the stability parameters for a ship sailing in a random sea. The random decrement is calculated from the random roll response. This equation has been shown to resemble the differential equation describing the free rolling motion. The nonlinearities in the free roll equation in addition to the linear damping term are lumped in one nonlinear function, F( , ), in the roll angle, , and velocity, . A feedforward network with a single hidden layer is then used to identify this general function. The function, F( , ) can be used to identify the general parameters in the righting moment using regression techniques. An example for applying this technique using model experiments for a series 60 block 60 model is presented. The agreement between curves predicted using neural network techniques and the actual curves is excellent.

  • Supplemental Notes:
    • OMAE 1995, 14th Intl Conf on Offshore Mechanics & Arctic Engng; 18-22 June 1995; Copenhagen, Denmark. Sponsored by ASME et al. Procs. Publ by ASME, ISBN 0-7918-1308-8. Vol II, p 127 [9 p, 13 ref, 1 tab, 4 fig]
  • Authors:
    • Haddara, M R
  • Publication Date: 1995

Language

  • English

Subject/Index Terms

Filing Info

  • Accession Number: 00718726
  • Record Type: Publication
  • Source Agency: British Maritime Technology
  • Files: TRIS
  • Created Date: Mar 27 1996 12:00AM