Naval Academy Armament

Shanghai, China

Naval Academy Armament

Shanghai, China

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Yang S.,National University of Defense Technology | Wang C.,Naval Academy Armament | Yang M.,National University of Defense Technology | Li G.,National University of Defense Technology | Huang K.,National University of Defense Technology
Communications in Computer and Information Science | Year: 2016

Appropriate missile selection for hostile aerial targets is conceived as an important issue in military operations research. However, both roughness and fuzziness may exist in military data simultaneously due to the complexity of situation and subjectivity of human knowledge. Therefore, this paper presents a two-stage decision model based on rough set theory (RST) and fuzzy inference system (FIS) for missile selection. The LEM2 algorithm in RST is applied to derive decision rules. Next, a Mamdani fuzzy inference system is formed to identify the proper missile type depending on the Gaussian membership functions. Some experiments with respect to some practical parameters are performed to validate the proposed model. The computational results indicate that the proposed model is capable of producing high-quality solutions and is convenient to be incorporated in a military decision support software. © Springer Science+Business Media Singapore 2016.

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