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Adaptive membership selection criteria using genetic algorithms for fuzzy Centroid localizations in wireless sensor networks
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نویسنده
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permpol s. ,rujirakul k. ,so-in c.
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منبع
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journal of telecommunication, electronic and computer engineering - 2016 - دوره : 8 - شماره : 6 - صفحه:113 -118
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چکیده
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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.
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کلیدواژه
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Adaptive membership function selection; Centroid; Fuzzy logic; Genetic algorithms; Wireless sensor networks
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آدرس
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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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Authors
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