A New Fuzzy Clustering Algorithm Based-on Adaptive Differential Evolution
Bei Yang - · Journal of Beijing Jiaotong University · 2009
Fuzzy C-means clustering(FCM) algorithm is a widely used algorithm in cluster analysis.However,as it is based on the gradient descent,FCM is essentially a local search algorithm.It is easy to fall into a local minimum,and is very sensitive to the initialization.In this paper,a new fuzzy clustering method based on an improved differential evolution algorithm was presented.First,the algorithm searches the approximate global optimal solution by the improved differential evolution,then the FCM algorithm is used for search in the optimal solution surrounding approximate solution.At the same time,an improvement is presented for reduce the impact of manual set parameters for DE algorithm.Experimental results shown that the proposed algorithm not only avoids the local optima and is robust to initialization,but also increases the convergence speed.