The code is written by Matlab, which is used for real-time prediction of rockburst intensity.
tSNE_dimension_reduction.m is used to reduce dimension of the database by tSNE algorithm.
KMeans_clustering_main.m is the main function of k-means algorithm, and KMeans_clustering.m is its sub function.
KMeans_plot.m is used to show clustering process under different iterations.
Canopy_clustering.m is used to determine the value of k in k-means algorithm in advance.
correlation.m is used to calculate the correlation coefficient between variables.
prediction_nopruning.m is used to train the precursor tree without pruning and predict rockburst intensity.
prediction_pruning.m is used to train the precursor tree with pruning and predict rockburst intensity.
bp_dr.m is used for dimension reduction in the engineering application phase, and initpop_generate.m, subpop_generate.m and ismature.m are its sub functions.
dist.m is used to assign clustering label in the engineering application phase.