Abstract:

Dynamic weapon-target assignment (WTA) problem is one of the critical problem when processing the battlefield command control and decision. The WTA algorithm makes the decision at the gap of two attack periods, which needs to be calculated efficiently.When using the battlefield assistant system to make WTA decision, it is a reasonable concept to utilize the machine learning method, make new decision from the known decision to avoid the need of searching new target assignment all over again. By using this concept, an interval type-2 fuzzy K-nearest neighbors(IT2FKNN) classifier usage on the WTA problem is proposed, by using the result from branch and bound to train the model, a parrallel IT2FKNN classifier is built to infer the assignment result. The proposed method is tested to be able to make a quick decision on the WTA problem.