Cluster’s risk evaluation based on fuzzy nearness degree

In view of the adverse effects of declining cluster, a method of evaluating risk level of mature cluster is developed. Through analyzing causes of declining, a risk indexes system is established. The features of clusterpsilas operation conditions with different risk levels are described. Owing to the complexity and uncertainty of cluster system, a TOPSIS comprehensive evaluation method based on fuzzy nearness degree is proposed. Firstly, asymmetry nearness degree between risk indexes system and operation conditions are calculated. Secondly, according to the method of TOPSIS, the positive and negative ideal grades are defined. Finally, symmetry nearness degrees between each operation condition and ideal grades are calculated and compared to determine the risk level of mature cluster. An example is given to show the feasibility of the method.