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   Adaptive membership selection criteria using genetic algorithms for fuzzy Centroid localizations in wireless sensor networks  
   
نویسنده permpol s. ,rujirakul k. ,so-in c.
منبع journal of telecommunication, electronic and computer engineering - 2016 - دوره : 8 - شماره : 6 - صفحه:113 -118
چکیده    This paper investigates the effect of fuzzy inputs,i.e.,signal strength,of various known nodes,to fuzzy logic systems in order to derive a proper weight for centroid,properly used to approximate the location in wireless sensor networks with its key advantage on simplicity but with precision trade-off. due to a fluctuation behavior of location estimation precisions with respect to a diversity of various inputs,here,we propose the use of heuristic approach applying genetic algorithms with mutation and cross-over steps to adaptively seek the optimal solution - a proper number of membership functions for fuzzy logic systems in weighted centroid - to achieve higher location estimation accuracy. the performance of our methodology is effectively confirmed by the intensive evaluation on a large scale simulation in various topologies and node densities against fixed membership function scenarios including a traditional centroid.
کلیدواژه Adaptive membership function selection; Centroid; Fuzzy logic; Genetic algorithms; Wireless sensor networks
آدرس department of computer science,faculty of science,khon kaen university, Thailand, department of computer science,faculty of science,khon kaen university, Thailand, department of computer science,faculty of science,khon kaen university, Thailand
 
     
   
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