A novel neuro-fuzzy classification system design by a species-based hybrid algorithm

Ching Hung Lee*, Hsin Wei Chiu, Chung Ta Li

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a novel neuro-fuzzy classification system by a species-based hybrid of electromagnetism-like mechanism and back-propagation algorithms (SEMBP). The neuro-fuzzy classification system is constructed by an interval type-2 fuzzy neural system with asymmetric membership functions (AIT2FNS). The hybrid algorithm SEMBP combines the advantages of EM and BP algorithms. Three classification problems: the XOR data set, the breast cancer data set, and the Iris data set are used to illustrate the performance of our approach.

Original languageEnglish
Title of host publication2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Pages2748-2753
Number of pages6
DOIs
StatePublished - 2010
Event2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 - Qingdao, China
Duration: 11 Jul 201014 Jul 2010

Publication series

Name2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
Volume6

Conference

Conference2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010
CountryChina
CityQingdao
Period11/07/1014/07/10

Keywords

  • Asymmetric membership function
  • Classification
  • TSK type
  • Type-2 fuzzy neural system
  • Uniform initialization

Fingerprint Dive into the research topics of 'A novel neuro-fuzzy classification system design by a species-based hybrid algorithm'. Together they form a unique fingerprint.

  • Cite this

    Lee, C. H., Chiu, H. W., & Li, C. T. (2010). A novel neuro-fuzzy classification system design by a species-based hybrid algorithm. In 2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010 (pp. 2748-2753). [5580807] (2010 International Conference on Machine Learning and Cybernetics, ICMLC 2010; Vol. 6). https://doi.org/10.1109/ICMLC.2010.5580807