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Support vector machine (SVM) is an effective tool in deal with small sample, nonlinear and high dimension classification problems. In this paper, an improved pre-treatment binary-tree SVM is proposed to solve fault diagnosis. Furthermore an ensemble method is presented to establish ensemble SVM. Here the improved SVM is used as weak learning machine. The new ensemble SVM can improve the performance...
Fault diagnosis of blast furnace is a hot topic and has a very important practical significance and value. At the same time, rapid diagnosis of blast furnace fault is a difficult problem. In this paper, a novel strategy based on CLS-SVM is proposed to solve this problem. A modified discrete particle swarm optimization is applied to optimize the feature selection and the LS-SVM parameters. Fitness...
Since fault diagnosis of blast furnace is very important in manufacturing, in this paper, a new strategy based on NN-DPSO-SVM is proposed to solve it. Using the nearest neighbor principle deletes the useless samples so that the training set is pruned. A modified discrete particle swarm optimization is applied to optimize the feature selection and the SVM parameters so that the algorithm can improve...
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