  Decision-making is a process of choosing among alternative courses of action
for solving complicated problems where multi-criteria objectives are involved.
The past few years have witnessed a growing recognition of Soft Computing
technologies that underlie the conception, design and utilization of
intelligent systems. Several works have been done where engineers and
scientists have applied intelligent techniques and heuristics to obtain optimal
decisions from imprecise information. In this paper, we present a concurrent
fuzzy-neural network approach combining unsupervised and supervised learning
techniques to develop the Tactical Air Combat Decision Support System (TACDSS).
Experiment results clearly demonstrate the efficiency of the proposed
technique.
