Simulation research on parameters of fuzzy c-means algorithm

The clustering performance of FCM with different parameter values was studied and the most suitable parameter combination for manufacturing cell formation was concluded by simulation experiment with 20 literature data sets. The experiment result shows that: (1) with the increasing of fuzziness degree m, the clustering performance becomes worse in terns of grouping efficacy, and the clustering time decreases; (2) With the decreasing of stopping criterion , the number of infeasible solutions increases, and clustering time increases; (3) for higher grouping efficacy and shorter clustering time, degree of fuzziness should be assigned to 2 and stopping criterion should be assigned to 0.01.