Genetic type-2 self-organising fuzzy logic controller applied to anaesthesia

Y.-X. Liu, J.-S. Shieh, S.-Z. Fan, Faiyaz Doctor, K.-K. Jen

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

3 Citations (Scopus)

Abstract

In this paper, a novel genetic type-2 self-organising fuzzy logic controller (SOFLC) is proposed for anaesthesia control. The genetic type-2 SOFLC has a hierarchical structure consisting of three layers: a basic type-2 fuzzy logic controller, a self-organising mechanism for online adaption, and a genetic algorithm for offline optimisation. The genetic type-2 SOFLC is tested under different levels of environmental noise and compared with basic type-2 SOFLC that does not optimised. The results show that the proposed genetic type-2 SOFLC can perform better than the type-2 SOFLC in the presence of noise in terms of steady state error.
Original languageEnglish
Title of host publication2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI)
PublisherIEEE
Pages83-88
ISBN (Print)9781467396073
DOIs
Publication statusPublished - 2015
Event2015 Conference on Technologies and Applications of Artificial Intelligence - Tainan, Taiwan, Province of China
Duration: 20 Nov 201522 Nov 2015

Conference

Conference2015 Conference on Technologies and Applications of Artificial Intelligence
CountryTaiwan, Province of China
CityTainan
Period20/11/1522/11/15

Bibliographical note

The full text is not available on the repository.

Keywords

  • fuzzy control
  • genetic algorithms
  • medical control systems
  • neurocontrollers
  • self-organising feature maps
  • anaesthesia control
  • environmental noise
  • genetic algorithm
  • genetic type-2 SOFLC
  • genetic type-2 self-organising fuzzy logic controller
  • offline optimisation
  • online adaption
  • anaesthesia
  • self-organizing fuzzy logic controller
  • type-2 fuzzy sets
  • Genetic algorithms
  • Genetics
  • Indexes
  • Mathematical model
  • Muscles
  • Surgery
  • Training

Fingerprint Dive into the research topics of 'Genetic type-2 self-organising fuzzy logic controller applied to anaesthesia'. Together they form a unique fingerprint.

  • Cite this

    Liu, Y-X., Shieh, J-S., Fan, S-Z., Doctor, F., & Jen, K-K. (2015). Genetic type-2 self-organising fuzzy logic controller applied to anaesthesia. In 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI) (pp. 83-88). IEEE. https://doi.org/10.1109/TAAI.2015.7407083