Abstract
Due to the localization of the objective function of traditional fuzzy clustering algorithm, a novel adaptive objective function of fuzzy clustering is proposed, the new objective function integrates the clustering characteristic of input space and the real time approximate characteristic of output space. The extraordinary neural network to handle the fuzzy clustering algorithm is also proposed. The experimental results show that the new algorithm has better performance in stable convergent rate, convergent speed, and the initial condition sensitivity compared with traditional fuzzy clustering algorithm. The result illuminates the rationality of importing felicitous adaptive feedback factors into the objective function.
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