Advances in Soft Computing pp 53-64 | Cite as
TACDSS: Adaptation Using a Hybrid Neuro-Fuzzy System
Summary
Normally an intelligent decision support system is build to solve complex problems involving multi-criteria decisions. The knowledgebase is the vital part of the decision support system containing the knowledge or data that is used for decision-making. 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 hybrid neuro-fuzzy technique for the adaptive learning of Takagi-Sugeno type fuzzy if-then rules for the Tactical Air Combat Decision Support System (TACDSS). Experiment results clearly demonstrate the efficiency of the proposed technique. Some simulation results demonstrating the difficulties to decide the optimal number and shape of the membership functions are also provided.
Keywords
Membership Function Decision Support System Fuzzy Rule Fuzzy Inference System Danger SituationPreview
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