Dengue outbreak prediction: hybrid meta-heuristic model

Parameter tuning of Leas Squares Support Vector Machines (LSSVM) hyper-parameters, namely regularization parameter and kernel parameters plays a crucial role in obtaining a promising result in prediction task. Any improper values setting of the said hyper-parameters would demote the generalization o...

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Main Authors:	Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda, Yuhanis, Yusof, Mohamad Farhan, Mohamad Mohsin
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2018
Subjects:	QA Mathematics QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/22085/ http://umpir.ump.edu.my/id/eprint/22085/1/17.%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf http://umpir.ump.edu.my/id/eprint/22085/2/17.1%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf

id	ump-22085
recordtype	eprints
spelling	ump-220852018-11-15T08:35:24Z http://umpir.ump.edu.my/id/eprint/22085/ Dengue outbreak prediction: hybrid meta-heuristic model Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda Yuhanis, Yusof Mohamad Farhan, Mohamad Mohsin QA Mathematics QA76 Computer software Parameter tuning of Leas Squares Support Vector Machines (LSSVM) hyper-parameters, namely regularization parameter and kernel parameters plays a crucial role in obtaining a promising result in prediction task. Any improper values setting of the said hyper-parameters would demote the generalization of LSSVM. Concerning that matter, in this study, Flower Pollination Algorithm (PA), which is relatively new optimization algorithm is hybrid with LSSVM. Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. Since it was first recognized, until now Dengue Fever (DF) remains as a major concern of public health in community, specifically during the massive outbreaks. A serious infection of dengue can progress into a more critical condition namely Dengue Hemorrhagic Fever (DHF). Therefore, a good prediction model is vital to predict the dengue outbreak cases. By using monthly disease surveillance and meteorological data, the performance of the prediction model is guided by Mean Square Error (MSE) and Root Mean Square Percentage Error (RMSPE). Findings of the study demonstrate that FPA-LSSVM is able to produce lower error rate compared to the other identified algorithms. Institute of Electrical and Electronics Engineers Inc. 2018-08 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22085/1/17.%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf pdf en http://umpir.ump.edu.my/id/eprint/22085/2/17.1%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf Zuriani, Mustaffa and Mohd Herwan, Sulaiman and Ernawan, Ferda and Yuhanis, Yusof and Mohamad Farhan, Mohamad Mohsin (2018) Dengue outbreak prediction: hybrid meta-heuristic model. In: 19th IEE/ACIS International Conference On Software Engineering, Artificial Intelligence,Networking And Parallel/Distributed Computing (SNPD 2018), 27 - 29 June 2018 , Busan, Korea. pp. 1-4.. ISBN 978-153865889-5
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	QA Mathematics QA76 Computer software
spellingShingle	QA Mathematics QA76 Computer software Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda Yuhanis, Yusof Mohamad Farhan, Mohamad Mohsin Dengue outbreak prediction: hybrid meta-heuristic model
description	Parameter tuning of Leas Squares Support Vector Machines (LSSVM) hyper-parameters, namely regularization parameter and kernel parameters plays a crucial role in obtaining a promising result in prediction task. Any improper values setting of the said hyper-parameters would demote the generalization of LSSVM. Concerning that matter, in this study, Flower Pollination Algorithm (PA), which is relatively new optimization algorithm is hybrid with LSSVM. Here, the FPA is served as an optimization algorithm for LSSVM. The hybrid FPA-LSSVM is later realized for prediction of dengue outbreak in Yogyakarta, Indonesia. Since it was first recognized, until now Dengue Fever (DF) remains as a major concern of public health in community, specifically during the massive outbreaks. A serious infection of dengue can progress into a more critical condition namely Dengue Hemorrhagic Fever (DHF). Therefore, a good prediction model is vital to predict the dengue outbreak cases. By using monthly disease surveillance and meteorological data, the performance of the prediction model is guided by Mean Square Error (MSE) and Root Mean Square Percentage Error (RMSPE). Findings of the study demonstrate that FPA-LSSVM is able to produce lower error rate compared to the other identified algorithms.
format	Conference or Workshop Item
author	Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda Yuhanis, Yusof Mohamad Farhan, Mohamad Mohsin
author_facet	Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda Yuhanis, Yusof Mohamad Farhan, Mohamad Mohsin
author_sort	Zuriani, Mustaffa
title	Dengue outbreak prediction: hybrid meta-heuristic model
title_short	Dengue outbreak prediction: hybrid meta-heuristic model
title_full	Dengue outbreak prediction: hybrid meta-heuristic model
title_fullStr	Dengue outbreak prediction: hybrid meta-heuristic model
title_full_unstemmed	Dengue outbreak prediction: hybrid meta-heuristic model
title_sort	dengue outbreak prediction: hybrid meta-heuristic model
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/22085/ http://umpir.ump.edu.my/id/eprint/22085/1/17.%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf http://umpir.ump.edu.my/id/eprint/22085/2/17.1%20Dengue%20outbreak%20prediction%20-hybrid%20meta-heuristic%20model.pdf
first_indexed	2023-09-18T22:32:41Z
last_indexed	2023-09-18T22:32:41Z
_version_	1777416391175962624

Dengue outbreak prediction: hybrid meta-heuristic model

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