Title: Avian influenza (H5N1) expert system using Dempster-Shafer theory

Authors: Andino Maseleno; Md. Mahmud Hasan

Addresses: Department of Computer Science, Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong BE 1410, Negara, Brunei Darussalam. ' Department of Computer Science, Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Gadong BE 1410, Negara, Brunei Darussalam

Abstract: Based on cumulative number of confirmed human cases of avian influenza (H5N1) reported to World Health Organization (WHO) in 2011 from 15 countries, Indonesia has the largest number of deaths because of avian influenza which 146 deaths. In this research, the researcher built an avian influenza (H5N1) expert system for identifying avian influenza disease and displaying the result of identification process. In this paper, we describe five symptoms as major symptoms which include depression, combs, wattle, bluish face region, swollen face region, narrowness of eyes, and balance disorders. We use chicken as research object. Dempster-Shafer theory is to quantify the degree of belief as inference engine in expert system, our approach uses Dempster-Shafer theory to combine beliefs under conditions of uncertainty and ignorance, and allows quantitative measurement of the belief and plausibility in our identification result. The result reveals that avian influenza (H5N1) expert system has successfully identified the existence of avian influenza and displaying the result of identification process.

Keywords: avian influenza; avian flu; bird flu; H5N1 identification; expert systems; uncertainty; ignorance; Dempster-Shafer theory; avian flu symptoms; chickens.

DOI: 10.1504/IJICT.2012.048766

International Journal of Information and Communication Technology, 2012 Vol.4 No.2/3/4, pp.227 - 241

Available online: 29 Aug 2012 *

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