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An Emergency Model of Home Network Environment Based on Genetic Algorithm

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Knowledge-Based Intelligent Information and Engineering Systems (KES 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3682))

Abstract

In this paper, we proposed an emergency model of home network environment based on genetic algorithm. This model can not only adapt the home network environment by using genetic algorithm but also detect the emergency events automatically. There are four modules in this model, saying, training knowledge base (TKB), genetic operator module (GOM), emergency knowledge base (EKB), and emergency early warning module (EEWM). TKB receives the messages from the environment and provides them for GOM to train EKB. GOM trains the EKB to fit the real situation by using genetic algorithm. EKB includes the database and the rule base which can provide messages for EEWM to infer. EEWM determines the emergency situations by fuzzy inferences and sends the caution messages to the users by mobile devices. Via this model, our home network environment will become more reliable and safer.

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Author information

Authors and Affiliations

  1. Department of Information Management, Chinese Culture University, 55, Hwa-Kung Road, Yang-Ming-San, Taipei, (11114), Taiwan

    Huey-Ming Lee & Shih-Feng Liao

Authors
  1. Huey-Ming Lee
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  2. Shih-Feng Liao
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Editor information

Editors and Affiliations

  1. School of Business, La Trobe University, 3086, Melbourne, Victoria, Australia

    Rajiv Khosla

  2. Centre for SMART systems Engineering Research Centre, University of Brighton, BN2 4GJ, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  3. School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Mawson Lakes, SA, Australia

    Lakhmi C. Jain

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© 2005 Springer-Verlag Berlin Heidelberg

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Lee, HM., Liao, SF. (2005). An Emergency Model of Home Network Environment Based on Genetic Algorithm. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552451_172

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  • DOI: https://doi.org/10.1007/11552451_172

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28895-4

  • Online ISBN: 978-3-540-31986-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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