Fuzzy Neural Tree for Knowledge Driven Design

A neural tree structure is considered with nodes of neuronal type, which is a Gaussian function playing the role of membership function. The total tree structure effectively works as a fuzzy logic model with inputs and outputs. In this model the locations of the fuzzy membership functions are normalized to unity so that the system has several desirable features and it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modelling properties and addressing complexity issues at the same time. A demonstrative application exercise of the model is presented and the favourable performance is demonstrated.