Abstract
For the purposes of real time and accuracy characteristics in air combat, the granular computing theory is introduced to the tactics decision analysis in cooperative team air combat, and a new approach to intelligent decision based on tolerance granularity space model is presented. A complex problem can be divided into several smaller ones, which are easily understood and solved according to the ideal of granular computing. The tolerance granularity space model is constructed by means of the inner-class distance defined in the attributes space. A variety of tactical information is effectively mapped into different granular layers in order to achieve the correct classification for tactics. In order to enhance the decision accuracy, a reduction method of tactics features based on granular computing is proposed, which directly gets the best and minimal reduction set to construct the tolerance granularity space model for the best decision accuracy. The simulation results show the model is endowed with better decision performance than the integration model of rough sets and neural networks.
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Acknowledgments
This study is supported by “863 National High-Tech Program of China” (No. 2010AA8090514C).
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© 2014 Springer-Verlag Berlin Heidelberg
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Meng, D., Wang, Y., Chen, Y., Zhong, L. (2014). Tactics Decision-Making Based on Granular Computing in Cooperative Team Air Combat. In: Wen, Z., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54927-4_88
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DOI: https://doi.org/10.1007/978-3-642-54927-4_88
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