Decision support systems using hybrid neurocomputing

This paper suggests a decision support system for tactical air combat environment where not much prior information is available about the decision regions. We proposed a combination of unsupervised learning for clustering the data (to develop decision regions) and a feed forward neural network to classify the decision regions accurately. The clustered data is used as the inputs to the multi-layered feed forward neural network, which is trained using several higher order learning paradigms. Experiment results reveal that the proposed method is efficient. (C) 2004 Elsevier B.V. All rights reserved.