Study of urban traffic congestion judgment based on FFCM clustering
基于FFCM聚类的城市交通拥堵判别研究

In order to solve the problem of urban traffic congestion judgment,a fast fuzzy C-means(FFCM) clustering method integrating hard C-means clustering method and fuzzy C-means clustering method was put forward.In this algorithm,the result of HCM clustering is the basis of the initial value of FFCM,which can speed-up its convergence.Then it's applied to a set of real traffic flow data.The clustering result shows that this method enjoy good performance in fast and effective distinguishing urban traffic congestion and will contribute to dynamic traffic congestion warning and traffic guidance.