Machine learning in engineering design - An unsupervised fuzzy neural network case-based learning model

Abstract

Engineering design is a creative and experience oriented process. Facing a new design case, an experienced designer will recall the similar cases in case base been solved before. Then, the designer will attempt to find the solution from these similar cases in a way of adaptation or synthesis. In this paper, an unsupervised fuzzy neural network (UFN) case-based learning model has been developed to perform the aforementioned design process and implemented in two steps. The UFN learning model has been applied to the domain of engineering design. The learning results show that the learning performance of the new learning model is superior to that of a supervised learning model only in complicated or discrete domains. Also, the unsupervised fuzzy neural network learning model can learn complicated design problems within a reasonable CPU time.