A self-tuning emergency model of home network environment

Authors:
Huey-Ming Lee;Shih-Feng Liao;Tsang-Yean Lee;Mu-Hsiu Hsu;Jin-Shieh Su
Affiliations:
Department of Information Management, Chinese Culture University, Taipei, Taiwan;Department of Information Management, Chinese Culture University, Taipei, Taiwan;Department of Information Management, Chinese Culture University, Taipei, Taiwan;Department of Information Management, Chinese Culture University, Taipei, Taiwan;Department of Information Management, Chinese Culture University, Taipei, Taiwan
Venue:
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Year:
2006

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Abstract

In this paper, we proposed a self-tuning emergency model of home network environment (SEMHNE). This model can not only tune the scaling factors and membership functions to fit the home network environment but also detect the emergency events automatically. There are three modules in this model, namely, emergency report module (ERM), renewable emergency rule base (RERB), and evolutionary database (EDB). ERM determines the emergency situations by fuzzy inferences and sends the warning message to the users. RERB can provide rules to ERM for inference. EDB can do self-tuning by using genetic algorithm and provide information to ERM for inference. Via this model, our home network environment will become more reliable and safety.