The evolution of the evolving neuro-fuzzy systems: from expert systems to spiking-, neurogenetic-, and quantum inspired

Date
2013
Authors
Kasabov, N
Supervisor
Item type
Chapter in Book
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract

This chapter follows the development of a class of intelligent information systems called evolving neuro-fuzzy systems (ENFS). ENFS combine the adaptive/ evolving learning ability of neural networks and the approximate reasoning and linguistically meaningful explanation features of fuzzy rules. The review includes fuzzy expert systems, fuzzy neuronal networks, evolving connectionist systems, spiking neural networks, neurogenetic systems, and quantum inspired systems, all discussed from the point of few of fuzzy rule interpretation as new knowledge acquired during their adaptive/evolving learning. This review is based on the author’s personal (evolving) research, integrating principles from neural networks, fuzzy systems and nature.

Description
Keywords
Source
On Fuzziness: Studies in Fuzziness and Soft Computing Volume 298, 2013, pp 271-280
Publisher's version
Rights statement
An author may self-archive an author-created version of his/her article on his/her own website and or in his/her institutional repository. He/she may also deposit this version on his/her funder’s or funder’s designated repository at the funder’s request or as a result of a legal obligation, provided it is not made publicly available until 12 months after official publication. He/ she may not use the publisher's PDF version, which is posted on www.springerlink.com, for the purpose of self-archiving or deposit. Furthermore, the author may only post his/her version provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at www.springerlink.com”. (Please also see Publisher’s Version and Citation).