A training technique for fuzzy number neural networks

A new technique is discussed for the training of fuzzy neural networks with general fuzzy number inputs, weights, and outputs. Fuzzy number neural networks are difficult to train because of the many alpha-cut constraints implied by the fuzzy weights. In this paper, an unconstrained representation is used for the fuzzy weights, allowing application of a standard backpropagation approach. The technique is demonstrated on a moderately large problem.