Abstract: The clustering method based on fuzzy equivalence matrix is one of the classical methods of fuzzy clustering. We applied it to assort wireless sensors for the first time. The algorithm analyzes the pertinence of two sensors with the Euclid distance of them, and then acquires the fuzzy equivalence matrix for subsection. We designed the algorithm, ana- lyzed the time complexity of i1_ And the algorithm was simulated on Matlab. The results of simulation show the wireless sensors are assorted several classes by different distributing density with the algorithm.

Key words: Fuzzy clustering, Wireless sensor, Pertinence, Fuzzy equivalence matrix