Akademik Veri Yönetim Sistemi
2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021, Kocaeli, Türkiye, 25 - 27 Ağustos 2021
© 2021 IEEE.The aim of Weapon-Target Assignment (WTA) problem is to assign weapons to the targets for intercept -or eliminatethe target in a most effective way. The objects of the problem - weapons and targets- are generally modeled with their properties like hit probability, and an algorithm -mostly optimization algorithm- is used to make that assignment with respect to the defined objective. For a more accurate WTA -dynamic- problem these objects should be modeled with additional algorithms. The WTA problem should contain movement models and decision systems. The weapons can be assigned to the targets such that they can learn the problem, also the targets can be decide the movement on the battlefield with respect to the other target's position and dangerous -previously hit- positions. Targets can move to a location where they can pose more danger. Therefore in this research the weapons and targets are modeled with evolving neural networks, separately. By this way, a more realistic model of the battlefield is obtained. In addition to that aim, the inverse WTA problem can be considered where targets become the main object such that the movement of the targets are modeled with a evolving neural network where it is desired to damage the assets not targets.