An Improved Information Fusion Algorithm Based on SVM

The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and has high generalization ability. The model offers a kind of effective way for the information fusion problem of little sample, non-linear and high dimension. In this paper, mobile agent is applied to information fusion system. The model of OODA and the study method of information fusion system are improved. The model and an algorithm of information fusion based on the support vector machine are proposed. The experiment results show that this hierarchical and parallel SVM training algorithm is efficient to deal with large-scale classification problems and has more satisfying accuracy in classification precision.