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 language | English |
|---|---|
| Title of host publication | 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI) |
| Publisher | IEEE |
| Pages | 83-88 |
| ISBN (Print) | 9781467396073 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | 2015 Conference on Technologies and Applications of Artificial Intelligence - Tainan, Taiwan, Province of China Duration: 20 Nov 2015 → 22 Nov 2015 |
Conference
| Conference | 2015 Conference on Technologies and Applications of Artificial Intelligence |
|---|---|
| Country/Territory | Taiwan, Province of China |
| City | Tainan |
| Period | 20/11/15 → 22/11/15 |
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