Rough Fuzzy C-Means Clustering Algorithm Based on Self-adaptive Weights

This paper proposed RFCM clustering algorithm based on self-adaptive weights. According to different distance between every data object and clustering center, using improved arc cotangent function to redistribute the distance, acquiring adaptive weights through the equivalence factor in each iteration, then carrying out RFCM clustering algorithm. The simulations are performed on synthetic and UCI data sets, and the results show the validity of the proposed algorithm. Furthermore, the proposed algorithm is applied in sorting radar signal, and the results show the practicability of the proposed algorithm.