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A Concurrent Neural Network - Genetic Programming Model For Decision Support Systems

In: Knowledge Management Nurturing Culture, Innovation, and Technology

Author

Listed:
  • AJITH ABRAHAM

    (School of Computer Science and Engineering, Chung-Ang University, Korea)

  • CRINA GROSAN

    (Department of Computer Science, Babes-Bolyai University, Cluj-Napoca, Romania)

  • CONG TRAN

    (School of Electrical and Information Engineering, University of South Australia, Australia)

  • LAKHMI JAIN

    (School of Electrical and Information Engineering, University of South Australia, Australia)

Abstract

This paper suggests a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and 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 is used as the inputs to the genetic programming algorithms. Some simulation results demonstrating the difference of these techniques and are also performed. Experiment results reveal that the proposed method is efficient.

Suggested Citation

  • Ajith Abraham & Crina Grosan & Cong Tran & Lakhmi Jain, 2005. "A Concurrent Neural Network - Genetic Programming Model For Decision Support Systems," World Scientific Book Chapters, in: Suliman Hawamdeh (ed.), Knowledge Management Nurturing Culture, Innovation, and Technology, chapter 20, pages 231-245, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812701527_0020
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