ABIRAMI, T and THANGARAJ, P.
Department of Computer Technology, Kongu Engineering College, Perundurai, Erode, India.
2Dept. of CSE, Bannariamman Institute of Technology, Sathy, Tamilnadu, India,
Abstract: As wireless sensor networks (WSN) generate a huge amount of data for varied applications, it is important to locate essential knowledge from it. WSN data is generally generated in streams before being forwarded to a sink. WSN performance in adversely affected as raw data leads to higher communication overhead. Frequent patterns are located through association mining. Hence, WSN network data have association mining applied to it only regular raw data patterns are forwarded to the sink which in turn lowers communication overhead. This paper proposes WSN data mining using association rule to extricate patterns. A Fuzzy based genetic algorithm along with the rule is used for efficient extraction.
[ABIRAMI, T,THANGARAJ, P. Association Rules for Wireless Sensor Data Based On Fuzzy - Genetic Algorithm. Life Sci J 2013;10(4s):554-558] (ISSN: 1097-8135). http://www.lifesciencesite.com. 84
Key words: Wireless Sensor Networks (WSN), Association rules, Genetic Algorithm, Fuzzy Logic.