The traditional support vector machines only deals with the binary classification. It has difficulty in solving the multi-class classification problem like the shift decision for the automatic transmission of the engineering vehicle. A shift decision algorithm that based on SVM-binary tree was presented. This method distributed classifier to nodes that constituted multi-class SVM. The number of SVM classifier and duplicated training samples could be reduced. The optimal shifting gear could be decided by the proposed approach, and the requirement of the engineering vehicle to the automatic shifting could be satisfied in time and accurately. The experiment showed that the support vector machines based on binary tree achieved better results than RBF neural network with genetics.
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韩顺杰,赵丁选.多类分类SVM在工程车辆自动变速挡位决策中的应用[J].农业机械学报,2007,38(2):10-12.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(2):10-12.