Modeling the Influence of Disturbances in High-Speed Railway Systems

Algorithm 1

K-Means algorithm.

Input: dataset , and initial centers K;

Output: categories of every sample

Initialization: Randomly classify samples as K categories, and calculate the

initial mean vector ();

Repeating the following step until stopping condition is satisfied:

(i) Calculating the sign () of sample ,

(ii) Classifying into its nearest cluster,

(iii) Updating the mean vector,

(iv) Stopping condition: mean vectors do not change, thus: