Adaptation of Mamdani Fuzzy Inference System Using Neuro - Genetic Approach for Tactical Air Combat Decision Support System

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dc.creatorTran, Cong
dc.creatorJain, Lakhmi
dc.creatorAbraham, Ajith
dc.date2004-05-06
dc.date.accessioned2026-07-07T03:21:14Z
dc.date.available2026-07-07T03:21:14Z
dc.descriptionNormally a decision support system is build to solve problem where multi-criteria decisions are involved. The knowledge base is the vital part of the decision support 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 a Mamdani fuzzy inference system for the Tactical Air Combat Decision Support System (TACDSS). Some simulation results demonstrating the difference of the learning techniques and are also provided.
dc.identifierhttps://arxiv.org/abs/cs/0405031
dc.identifierhttp://arxiv.org/abs/cs/0405031
dc.identifier15th Australian Joint Conference on Artificial Intelligence (AI'02) Australia, LNAI 2557, Springer Verlag, Germany, pp. 672-679, 2002
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32116
dc.subjectArtificial Intelligence
dc.subject1.2.0
dc.titleAdaptation of Mamdani Fuzzy Inference System Using Neuro - Genetic Approach for Tactical Air Combat Decision Support System
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