Adaptation of a Mamdani fuzzy inference system using neuro-genetic approach for Tactical Air Combat Decision Support System

Abstract

Normally a decision support system is build to solve problems where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support system containing the information or data that is used in decision-making process. This is the field where engineers and scientists have applied several intelligent techniques and heuristics to obtain optimal decisions from imprecise information. In this paper, we present a hybrid neuro-genetic learning approach for the adaptation of a Mamdani fuzzy inference system for the Tactical Air Combat Decision Support System (TACDSS). Some simulation results demonstrating the different learning techniques are also provided.