AN ARTIFICIAL NEURAL NETWORK MODEL FOR PRELIMINARY SHIP DESIGN

A preliminary ship design framework is developed which consists of a set of interconnected neural networks (multilayer perceptrons) undergoing supervised training. The model proceeds to generate from the owners requirements, the set of principal dimensions, form coefficients with the estimates of steel, outfit and machinery weight, power requirement, capacity etc. The Modified Marquardt Levenberg Algorithm has been implemented for the minimization of the error in prediction which allows a faster training of the network. The neural network model in the preliminary design framework can thus be used for a quick appraisal of ship design. A containership design has been taken to illustrate the design principles and the behaviour of the neural network model in the ship design framework.

  • Supplemental Notes:
    • ICCAS 94, 8th Intl Conf on Computer Applications in Shipbuilding; 5-9 Sept 1994; Bremen, Germany. Sponsored by Bremer Vulkan Verbund AG and Kockums Computer Systems AB. Procs. Publ by Berry Rasmusson Reklam AB, Sweden, ISBN 91- 630-2762-3. Vol 2, p 10.15 [16 p, 19 ref, 2 tab, 4 fig]
  • Authors:
    • Sha, O P
    • Ray, T
    • Gokarn, R P
  • Publication Date: 1994

Language

  • English

Subject/Index Terms

Filing Info

  • Accession Number: 00710822
  • Record Type: Publication
  • Source Agency: British Maritime Technology
  • Files: TRIS
  • Created Date: Aug 14 1995 12:00AM