Abstract
This study is devoted to a new class of models of fuzzy consensus exploiting the paradigm of fuzzy neurocomputing. In comparison to standard neural networks, the proposed networks form an important and conceptually rich environment whose constructs exhibit a significant logical transparency augmented by profound learning capabilities. Numerical studies are also provided.
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Pedrycz, W. (1997). The Development of Fuzzy Consensus via Neural Modelling. In: Kacprzyk, J., Nurmi, H., Fedrizzi, M. (eds) Consensus Under Fuzziness. International Series in Intelligent Technologies, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6333-4_10
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DOI: https://doi.org/10.1007/978-1-4615-6333-4_10
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