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Choosing of battle position through training support vector machines

The battlefield environment affects maneuvers and the war situation. We choose the battle position through a training support vector machine (SVM). We give firstly the method of two-class classification by means of SVM. Choosing of battle position is a problem of multi-class classification, so we adopt a "divide and conquer" approach to train the data set. We use recursively SVM until the result meets the condition of battle position. In the course of training the data, we use one-against-one and decision tree methods. Using the schemes, we select the suited battle position and get better effect.