Data analysis and utilization method based on genetic programming in ship design

Authors:
Kyung Ho Lee;Yun Seog Yeun;Young Soon Yang;Jang Hyun Lee;June Oh
Affiliations:
Department of Naval Architect & Ocean, Engineering, Inha University, Inchon, Korea;Department of Mechanical Design Engineering, Daejin University, Pocheon, Kyonggi-do, Korea;Department of Naval, Architecture & Ocean Engineering, Seoul National University, Seoul, Korea;Department of Naval Architect & Ocean, Engineering, Inha University, Inchon, Korea;Department of Naval Architect & Ocean, Engineering, Inha University, Inchon, Korea
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
Year:
2006

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Abstract

Although Korean shipyards have accumulated a great amount of data, they do not have appropriate tools to utilize the data in practical works. Engineering data contains the experiences and know-how of experts. Data mining technique is useful to extract knowledge or information from the accumulated existing data. This paper presents a machine learning method based on genetic programming (GP), which can be one of the components for the realization of data mining. The paper deals with linear models of GP for regression or approximation problems when the given learning samples are not sufficient.