A K-harmonic Means Clustering Algorithm Based on Enhanced Differential Evolution

The conventional K-harmonic means is tend to be trapped by local optima. To resolve this problem, a novel K-harmonic means clustering algorithm using enhanced differential evolution technique is proposed. This algorithm improves the global search ability by applying Laplace mutation operator and logarithmically crossover probability operator. Numerical experiments show that this algorithm overcomes the disadvantages of the K-harmonic means, and improves the global search ability.