Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/97929
Title: | A novel brain-inspired neuro-fuzzy hybrid system for artificial ventilation modeling | Authors: | Ng, G. S. Liu, F. Loh, T. F. Quek, Chai |
Keywords: | DRNTU::Engineering::Computer science and engineering | Issue Date: | 2012 | Series/Report no.: | Expert systems with applications | Abstract: | Artificial ventilation is a crucial supporting treatment for Intensive Care Unit. However, as the ventilator control becomes increasingly more complex, it is non-trivial for less experienced clinicians to control the settings. In this paper, the novel Hebbian based Rule Reduction (HeRR) neuro-fuzzy system is applied to model this control problem for intra-patient and inter-patient ventilator control. These two ICU care studies demonstrate the capability of HeRR neuro-fuzzy system in extracting the salient knowledge embedded in the training data. Experimental results on the two studies show promising use of the HeRR neuro-fuzzy system for artificial ventilation. | URI: | https://hdl.handle.net/10356/97929 http://hdl.handle.net/10220/11234 |
DOI: | 10.1016/j.eswa.2012.01.028 | Schools: | School of Computer Engineering | Research Centres: | Centre for Computational Intelligence | Rights: | © 2012 Published by Elsevier Ltd. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
SCOPUSTM
Citations
50
2
Updated on Mar 26, 2024
Web of ScienceTM
Citations
50
2
Updated on Oct 24, 2023
Page view(s) 50
505
Updated on Mar 28, 2024
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.