Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97929
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dc.contributor.authorNg, G. S.en
dc.contributor.authorLiu, F.en
dc.contributor.authorLoh, T. F.en
dc.contributor.authorQuek, Chaien
dc.date.accessioned2013-07-11T08:12:03Zen
dc.date.accessioned2019-12-06T19:48:26Z-
dc.date.available2013-07-11T08:12:03Zen
dc.date.available2019-12-06T19:48:26Z-
dc.date.copyright2012en
dc.date.issued2012en
dc.identifier.urihttps://hdl.handle.net/10356/97929-
dc.description.abstractArtificial 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.en
dc.language.isoenen
dc.relation.ispartofseriesExpert systems with applicationsen
dc.rights© 2012 Published by Elsevier Ltd.en
dc.subjectDRNTU::Engineering::Computer science and engineeringen
dc.titleA novel brain-inspired neuro-fuzzy hybrid system for artificial ventilation modelingen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Computer Engineeringen
dc.contributor.researchCentre for Computational Intelligenceen
dc.identifier.doi10.1016/j.eswa.2012.01.028en
item.fulltextNo Fulltext-
item.grantfulltextnone-
Appears in Collections:SCSE Journal Articles

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