Application of binary tree multi-class classification algorithm based on SVM in shift decision for engineering vehicle

Support Vector Machines (SVM) based on structural risk minimization principle demonstrates the better learning ability for decision-making. Since the normal SVM is deduced from two classifications, it faced difficulty in solving the multi-class classifications like the shift decision of the engineering vehicle. Here we present shift decision algorithm which is based on SVM -binary tree multi-class classification. It distributes classifier to every node for constructing the multi-class SVM. Experiments show that the method can optimize the gear shift position according to operation states, consequently, meet the needs of the automatic shift transmission accurately and on time. It is an effective way to realize the intelligence shift decision for engineering vehicle.