UMP Institutional Repository

Dengue outbreak prediction using an improved salp swarm algorithm

Khairunnisa Amalina, Mohd Rosli and Zuriani, Mustaffa and Yuhanis, Yusof and Mohamad Farhan, Mohamad Mohsin (2020) Dengue outbreak prediction using an improved salp swarm algorithm. In: 6th International Conference on Software Engineering & Computer Systems (ICSECS), 25 - 27 September 2019 , Vistana City Center, Kuantan, Pahang, Malaysia. pp. 1-5., 769 (1). ISSN 1757-8981

[img] Pdf
113. Dengue outbreak prediction using an improved salp swarm algorithm.pdf
Restricted to Repository staff only

Download (163kB) | Request a copy
[img]
Preview
Pdf
113.1 Dengue outbreak prediction using an improved salp swarm algorithm.pdf

Download (89kB) | Preview

Abstract

Dengue disease is the most common type of disease caused by mosquitoes. It is reported that dengue fever was first recognized in Thailand and Philippines in 1950. According to World Health Organization (WHO), dengue is a viral disease that spread in public environment where the number of cases reported in 2010 increased from 2.2 million to 3.2 million in 2015. Until today, numerous studies by researchers to improve the prediction of dengue fever disease based on Computational Intelligence (CI) methods have been reported. The research includes study using Swarm Intelligence (SI) algorithm. In this study, an improved Salp Swarm Algorithm (iSSA) is proposed for dengue outbreak prediction. The original SSA will be enhanced by enriching the exploration and exploitation process for the sake of improving the accuracy of dengue outbreak prediction. This will be done by inducing a mutation based on Levy Flight. Later, the iSSA algorithm will be realized on dengue disease dataset. The proposed iSSA will be compared against the original SSA and another CI method known as Grey Wolf Optimization (GWO). With this proposed algorithm, it is expected to improve the dengue outbreak prediction where MAE and RMSE are two crucial evaluation indicators when smaller the values obtained, more accurate the prediction model.

Item Type: Conference or Workshop Item (Lecture)
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Dengue outbreak prediction; Levy flight; Salp swarm slgorithm
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 01 Dec 2020 01:31
Last Modified: 01 Dec 2020 01:31
URI: http://umpir.ump.edu.my/id/eprint/27840
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item