Decision Support Systems Using Ensemble Genetic Programming

Ajith Abraham () and Crina Grosan ()
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Ajith Abraham: IITA Professorship Program, School of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, Republic of Korea
Crina Grosan: Department of Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania

Journal of Information & Knowledge Management (JIKM), 2006, vol. 05, issue 04, 303-313

Abstract: This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of three well-known genetic programming techniques to classify the different decision regions accurately. The genetic programming techniques used are: Linear Genetic programming (LGP), Multi-Expression Programming (MEP) and Gene Expression Programming (GEP). The clustered data are used as the inputs to the genetic programming algorithms. Some simulation results demonstrating the difference of these techniques are also performed. Test results reveal that the proposed ensemble method performed better than the individual GP approaches and that the method is efficient.

Keywords: Decision support systems; genetic programming; ensemble systems; evolutionary multi-objective optimisation (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1142/S0219649206001566

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