Comparison of different neural networks performances on motorboat datasets


AMASYALI M. F. , BAL M. , ÇELEBİ U. B. , EKİNCİ S. , Boyaci U. K.

21st International Symposium on Computer and Information Sciences (ISCIS 2006), İstanbul, Turkey, 1 - 03 November 2006, vol.4263, pp.212-220 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 4263
  • Doi Number: 10.1007/11902140_24
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.212-220

Abstract

Calculation of the required engine power and displacement takes an important place in the initial design of motorboats. Recently, several calculation methods with fewer parameters and with a possible gain of time compared to classical methods have been proposed. This study introduces a novel calculation method based on neural networks. The method requires less data input and hence is more easily applicable than classical methods. In this study several different neural network methods have been conducted on data sets which have principal parameters of motorboats and the respective performances have been presented. From the results obtained, displacement and engine power prediction for motor boats can be used at a suitable level for ship building industry.