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AI EDAM: Artificial Intelligence for Engineering Design, Analysis and Manufacturing

Table of Contents - 2003 - Volume 17, Issue 03  


Using genetic programming and decision trees for generating structural descriptions of four bar mechanisms

ANIKÓ  EKÁRT  a1 c1 and ANDRÁS  MÁRKUS  a1
a1 Computer and Automation Research Institute, Hungarian Academy of Sciences, Budapest, Hungary

Article author query
ekart a   [Google Scholar] 
markus a   [Google Scholar] 
 

Abstract

Four bar mechanisms are basic components of many important mechanical devices. The kinematic synthesis of four bar mechanisms is a difficult design problem. A novel method that combines the genetic programming and decision tree learning methods is presented. We give a structural description for the class of mechanisms that produce desired coupler curves. Constructive induction is used to find and characterize feasible regions of the design space. Decision trees constitute the learning engine, and the new features are created by genetic programming.

(Received April 15 2002)
(Accepted January 12 2003)


Key Words: Decision Trees; Four Bar Mechanism Synthesis; Genetic Programming; Machine Learning.

Correspondence:
c1 Reprint requests to: Anikó Ekárt, Computer and Automation Research Institute, Hungarian Academy of Sciences, PO Box 63, 1518 Budapest, Hungary. E-mail: ekart@sztaki.hu

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