In this paper, a novel hybrid method based on interval-valued fuzzy neural network for approximate of interval-valued fuzzy regression models, is presented.The work of this paper is an expansion of the research of real fuzzy Front Panel Escutcheon regression models.In this paper interval-valued fuzzy neural network (IVFNN) can be trained with crisp and interval-valued fuzzy data.Here a neural network is considered as a part of a large field called neural Ski de fond - Equipement - Skis - Enfant - Classic computing or soft computing.Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed.
Finally, we illustrate our approach by some numerical examples and compare this method with existing methods.