• Apr 24, 2017 News! Vol.6, No.4 has been indexed by EI (Inspec).   [Click]
  • Apr 24, 2017 News! Vol.6, No.3 has been indexed by EI (Inspec).   [Click]
  • Jun 26, 2017 News!Vol 7, No 4 has been published with online version 12 original aritcles from 6 countries are published in this issue   [Click]
General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2014Vol.4(2): 95-99 ISSN: 2010-3697
DOI: 10.7763/IJMO.2014.V4.353

The Research of Influenza H1N1’s Transmission Based on Artificial Society

Song Zhi Chao, Ge Yuan Zheng, Duan Hong, Meng Rong Qing, and Qiu Xiao Gang
Abstract—As the computer technology develops rapidly, the Artificial Society Method has been applied in lots of fields, which uses computers to build one virtual laboratory and studies the questions in it by experiments. This paper researches the transmission of influenza H1N1 which spreads globally. In this paper we construct a simple artificial village by building Agents and the hierarchical contact relationships among them firstly. Then activity rules of Agents are designed and the SEIR model is applied in the influenza H1N1’s transmission experiments. At last parameters and rules are set. How the initial number of the infected and the degree of the initial infected person in the contact network affect the transmission of the influenza H1N1 have been studied by two simulation experiments. The results show that the transmission speed and the number of the infected in experiments are positively correlated with the number of the initial infected and the degree of the initial infected person in the contact network.

Index Terms—Artificial society METHOD, influenza H1N1, SEIR, contact relationships.

The authors are with College of Information System and Management, National University of Defense Technology, Changsha, China (e-mail: song_zhichao@139.com).

[PDF]

Cite: Song Zhi Chao, Ge Yuan Zheng, Duan Hong, Meng Rong Qing , and Qiu Xiao Gang, "The Research of Influenza H1N1’s Transmission Based on Artificial Society," International Journal of Modeling and Optimization vol. 4, no. 2, pp. 95-99, 2014.

Copyright © 2008-2015.International Journal of Modeling and Optimization. All rights reserved.
E-mail: ijmo@iacsitp.com