Normally a decision support system is build to solve problem wheremulti-criteria decisions are involved. The knowledge base is the vital part ofthe decision support containing the information or data that is used indecision-making process. This is the field where engineers and scientists haveapplied several intelligent techniques and heuristics to obtain optimaldecisions from imprecise information. In this paper, we present a hybridneuro-genetic learning approach for the adaptation a Mamdani fuzzy inferencesystem for the Tactical Air Combat Decision Support System (TACDSS). Somesimulation results demonstrating the difference of the learning techniques andare also provided.
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