A course in fuzzy systems and control
A course in fuzzy systems and control
Fuzzy sets and their application to clustering and training
Fuzzy sets and their application to clustering and training
Electric Power Applications of Fuzzy Systems
Electric Power Applications of Fuzzy Systems
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
A Possibilistic Fuzzy c-Means Clustering Algorithm
IEEE Transactions on Fuzzy Systems
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
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This paper is to investigate the application of fuzzy c-means clustering to the direct identification of coherent synchronous generators in power systems. Because of the conceptual appropriateness and computational simplicity, this approach is essentially a fast and flexible method. At first, the coherency measures are derived from the time-domain responses of generators in order to reveal the relations between any pair of generators. And then they are used as initial element values of the membership matrix in the clustering procedures. An application of the proposed method to the Taiwan power (Taipower) system is demonstrated in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations, operating conditions, data sampling interval, and power system stabilizers are also investigated, as well. The results are compared with those obtained from the similarity relation method. And thus it is found that the presented approach needs less computation time and can directly initialize a clustering process for any number of clusters.