Utilizing an ensemble of SVMs with GMM voting-based mechanism in predicting dangerous seismic events in active coal mines

This paper presents an application of a Gaussian Mixture Model-based voting mechanism for an ensemble of Support Vector Machines (SVMs) to the problem of predicting dangerous seismic events in active coal mines. The author proposes a method of preparing an ensemble of SVMs with different parameters and using the “wisdom of the crowd” for a classification… (More)