Applications of neuro fuzzy systems: A brief review and future outline

Samarjit Kar, Sujit Das, Pijush Kanti Ghosh
2014 Applied Soft Computing  
This paper surveys neuro fuzzy systems (NFS) development using classification and literature review of articles for the last decade (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) to explore how various NFS methodologies have been developed during this period. Based on the selected journals of different NFS applications and different online database of NFS, this article surveys and classifies NFS applications into ten different categories such as student modeling system,
more » ... al system, economic system, electrical and electronics system, traffic control, image processing and feature extraction, manufacturing and system modeling, forecasting and predictions, NFS enhancements and social sciences. For each of these categories, this paper mentions a brief future outline. This review study indicates mainly three types of future development directions for NFS methodologies, domains and article types: (1) NFS methodologies are tending to be developed toward expertise orientation. (2) It is suggested that different social science methodologies could be implemented using NFS as another kind of expert methodology. (3) The ability to continually change and learning capability is the driving power of NFS methodologies and will be the key for future intelligent applications. (P.K. Ghosh). is why much relevant research has been conducted. AI methods are mainly comprised of fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro fuzzy systems, genetic fuzzy systems and genetic programming neural networks etc. Neuro-fuzzy systems refer to combinations of artificial neural network and fuzzy logic in the field of artificial intelligence, which was proposed by Jang [1] in 1993. The basic idea behind this NFS is that it combines human-like reasoning style of fuzzy systems with the learning and connectionist structure of neural networks. NFS 1568-4946/$ -see front matter
doi:10.1016/j.asoc.2013.10.014 fatcat:iochb6rlgbhb5dmpmx7jeh54mu