Neuro-Fuzzy Approaches to Decision Making: An Application to Check Authorization from Incomplete Informatio

V. K. Ramani, J. R. Echuaz, G. J. Vachtsevanos, and S. S. Kim

This paper describes the application of several neuro-fuzzy paradigms, such as a multilayer perceptron, a polynomial neural network, and a fuzzy decision model to the problem of check approval from incomplete data. A simple benchmark case is established as a performance metric to compare the various non-linear strategies. An overall Improvement of at least 10% w~ obtained in each of these cases.


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