A CONCURRENT NEURAL NETWORK - GENETIC PROGRAMMING MODEL FOR DECISION SUPPORT SYSTEMS

AbstractThis 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.

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