Framework for Automatic Development of Type 2 Fuzzy, Neuro and Neuro-Fuzzy Systems

Abstract

This paper presents the design and development of generic framework which aids creation of fuzzy, neural network and neuro fuzzy systems to provide expert advice in various fields. The proposed framework is based on neuro fuzzy hybridization. Artificial neural network of the framework aids learning and fuzzy part helps in providing logical reasoning for making proper decisions based on inference of domain expert’s knowledge. Hence by hybridizing neural network and fuzzy logic we obtain advantages of both the fields. Further the framework considered type 2 fuzzy logic for more human like approach. Developing a neuro fuzzy advisory system is tedious and complex task. Much of the time is wasted in developing computational logic and hybridizing the two methodologies. In order to generate a neuro fuzzy advisory system quickly and efficiently, we have designed a generic framework that will generate the advisory system. The resulting advisory system for the given domain is interactive with its user and asks question to generate fuzzy rules. The system also allows provision of training sets for neural network by its users in order to train the neural network. The paper also describes a working prototype implemented based on the designed framework; which can create a fuzzy system, a neural network system or a hybrid neuro fuzzy system according to information provided. The working of the prototype is also discussed with outputs in order to develop a fuzzy system, a neural network system and a hybrid neuro fuzzy system for a domain of course selection advisory. The generated systems through this prototype can be used on web or on desktop as per the user requirement.