Abstract
Battlefield environment affects maneuver and war situation. We choose the battle position though 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 "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 the decision tree methods. Using the schemes, we select the suited battle position and get better effect.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2002 International Conference on Machine Learning and Cybernetics |
| Pages | 18-20 |
| Number of pages | 3 |
| Publication status | Published - 2002 |
| Event | Proceedings of 2002 International Conference on Machine Learning and Cybernetics - Beijing, China Duration: 4 Nov 2002 → 5 Nov 2002 |
Publication series
| Name | Proceedings of 2002 International Conference on Machine Learning and Cybernetics |
|---|---|
| Volume | 1 |
Conference
| Conference | Proceedings of 2002 International Conference on Machine Learning and Cybernetics |
|---|---|
| Country/Territory | China |
| City | Beijing |
| Period | 4/11/02 → 5/11/02 |
Keywords
- Optimal separating hyperplane
- Support vector machine (SVM)
- Training algorithm
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Li, K., & Liu, Y. S. (2002). Choosing of battle position through training support vector machines. In Proceedings of 2002 International Conference on Machine Learning and Cybernetics (pp. 18-20). (Proceedings of 2002 International Conference on Machine Learning and Cybernetics; Vol. 1).