ANGIE: Adaptive Network for Granular Information and Evidence Processing

In this paper the possibility of using adaptive networks in fuzzy-evidence-based decision support systems is considered. The architecture and learning algorithm underlying ANGIE (adaptive network for granular information processing) is presented. The proposed learning procedure helps in solving a task that can be related to sensitivity analysis in decision aid models. The proposed adaptive network can be used as a decision support system or as a tool for determining the significance and contribution of fuzzy features to the reaching of the desired value of the fuzzy criterion.