Abstract
In order to analyze the stability of surrounding rock accurately and effectively, a rock classification method based on QGA (quantum genetic algorithm)-SVM (support vector machine) is put forward. QGA was used for global search in the solution space to optimize the kernel function parameters of SVM. And this method improved the classification accuracy of SVM in rock classification. Finally, a rock classification model based on QGA-SVM was established and applied to practical engineering. The result shows that the improved SVM has a higher accuracy in stability analysis of surrounding rock.
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