Deep neuro-fuzzy architectures

Anuar Dorzhigulov, Alex James Pappachen

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Fuzzy logic inspires from the non-deterministic behaviour of human brain computations. The fusion of neural networks and fuzzy logic such as neuro-fuzzy architectures is natural, as both represent elementary inspiration from brain computations involving learning, adaptation and ability to tolerate noise. This chapter focuses on neuro-fuzzy and alike solutions for machine learning from perspective of functionality, architectures and applications.

Original languageEnglish
Title of host publicationModeling and Optimization in Science and Technologies
PublisherSpringer Verlag
Pages195-213
Number of pages19
DOIs
Publication statusPublished - Jan 1 2020

Publication series

NameModeling and Optimization in Science and Technologies
Volume14
ISSN (Print)2196-7326
ISSN (Electronic)2196-7334

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ASJC Scopus subject areas

  • Modelling and Simulation
  • Medical Assisting and Transcription
  • Applied Mathematics

Cite this

Dorzhigulov, A., & James Pappachen, A. (2020). Deep neuro-fuzzy architectures. In Modeling and Optimization in Science and Technologies (pp. 195-213). (Modeling and Optimization in Science and Technologies; Vol. 14). Springer Verlag. https://doi.org/10.1007/978-3-030-14524-8_15