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Combining multiple neural networks by fuzzy integral for robust classification

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2 Author(s)
Sung-Bae Cho ; Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Taejon, South Korea ; J. H. Kim

In the area of artificial neural networks, the concept of combining multiple networks has been proposed as a new direction for the development of highly reliable neural network systems. The authors propose a method for multinetwork combination based on the fuzzy integral. This technique nonlinearly combines objective evidence, in the form of a fuzzy membership function, with subjective evaluation of the worth of the individual neural networks with respect to the decision. The experimental results with the recognition problem of on-line handwriting characters confirm the superiority of the presented method to the other voting techniques

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IEEE Transactions on Systems, Man, and Cybernetics  (Volume:25 ,  Issue: 2 )