Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease

Cardiovascular disease (CVD) remains a great concern in the field of healthcare. It is responsible for the highest mortality rate leading cause of death worldwide. This research utilizes an Adaptive neuro-fuzzy inference system (ANFIS) and addresses the problem of topology and parametric configurati...

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Main Author:	Jinjiri, Wada Mohammed
Format:	Thesis
Language:	English
Published:	2023
Subjects:	QA75.5-76.95 Electronic computers. Computer science
Online Access:	http://eprints.usm.my/60543/1/Pages%20from%20WADA%20MOHAMMED%20JINJIRI%20-%20TESIS.pdf http://eprints.usm.my/60543/
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Institution:	Universiti Sains Malaysia
Language:	English

id	my.usm.eprints.60543
record_format	eprints
spelling	my.usm.eprints.60543 http://eprints.usm.my/60543/ Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease Jinjiri, Wada Mohammed QA75.5-76.95 Electronic computers. Computer science Cardiovascular disease (CVD) remains a great concern in the field of healthcare. It is responsible for the highest mortality rate leading cause of death worldwide. This research utilizes an Adaptive neuro-fuzzy inference system (ANFIS) and addresses the problem of topology and parametric configurations that lead to the prediction error for CVD. 2023-06 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60543/1/Pages%20from%20WADA%20MOHAMMED%20JINJIRI%20-%20TESIS.pdf Jinjiri, Wada Mohammed (2023) Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease. Masters thesis, Universiti Sains Malaysia.
institution	Universiti Sains Malaysia
building	Hamzah Sendut Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Sains Malaysia
content_source	USM Institutional Repository
url_provider	http://eprints.usm.my/
language	English
topic	QA75.5-76.95 Electronic computers. Computer science
spellingShingle	QA75.5-76.95 Electronic computers. Computer science Jinjiri, Wada Mohammed Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
description	Cardiovascular disease (CVD) remains a great concern in the field of healthcare. It is responsible for the highest mortality rate leading cause of death worldwide. This research utilizes an Adaptive neuro-fuzzy inference system (ANFIS) and addresses the problem of topology and parametric configurations that lead to the prediction error for CVD.
format	Thesis
author	Jinjiri, Wada Mohammed
author_facet	Jinjiri, Wada Mohammed
author_sort	Jinjiri, Wada Mohammed
title	Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
title_short	Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
title_full	Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
title_fullStr	Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
title_full_unstemmed	Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease
title_sort	optimizing adaptive neuro fuzzy inference system (anfis) with dragonfly algorithm for cardiovascular disease
publishDate	2023
url	http://eprints.usm.my/60543/1/Pages%20from%20WADA%20MOHAMMED%20JINJIRI%20-%20TESIS.pdf http://eprints.usm.my/60543/
_version_	1800086046704140288

Optimizing Adaptive Neuro Fuzzy Inference System (Anfis) With Dragonfly Algorithm For Cardiovascular Disease

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