A decision fusion method of SVM-DS and its application in high-speed rail fault

In order to solve the difficulty of obtaining the Basic Probability Assignment(BPA) of DS evidence theory in the practical application, a decision fusion method combing SVM and DS evidence theory is proposed. The probability model of Platt is used to transform the hard outputs of different SVM classifiers into probability outputs, and the confusion matrices are used to calculate the local credibility of classifiers. The BPA function is established based on the posterior probability of SVM and local credibility of classifiers. Finally, the final decision is made through DS fusion based on BPA. Applying this method to the high-speed rail failure data, the experimental results show that the method of constructing BPA is effective and reasonable in practical problems, and the method of decision fusion can steadily improve the classification accuracy compared with the single classifier.