The New Method Definite Initial Cluster Center for Fuzzy Risk Clustering Neural Networks
Kaiqi Zou, Jie Cui · 2007
Neural network has a powerful parallel processing capability, along with its rise in the fuzzy risk cluster analysis which has occupied an important position, however, the quality of fuzzy risk clustering results is influenced by the initial value of options.The initial cluster center method for fuzzy risk clustering neural network, based on density and grid method, automatically determine the number of clusters and the initial cluster centers.Compared with the classical method simulation FCM, we can see a valid and effective method that can effectively speed up the convergence.