This paper presents a practical algorithm for training neuralnetworks with fuzzy number weights, inputs, and outputs. Typically,fuzzy number neural networks are difficult to train because of themany α-cut constraints implied by the fuzzy weights. Atransformation is used to eliminate these constraints and allow useof standard unconstrained optimization methods. The algorithm isdemonstrated on a three-layer network.
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