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- W2046128567 abstract "Location-based systems for indoor positioning have been studied widely owing to their application in various fields. The fingerprinting approach is often used in Wi-Fi positioning systems. The K-nearest-neighbor fingerprinting algorithm uses a fixed number of neighbors, which reduces positioning accuracy. Here, we propose a novel fingerprinting algorithm, the enhanced weighted K-nearest neighbor (EWKNN) algorithm, which improves accuracy by changing the number of considered neighbors. Experimental results show that the proposed algorithm gives higher accuracy." @default.
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- W2046128567 date "2012-10-31" @default.
- W2046128567 modified "2023-09-25" @default.
- W2046128567 title "Enhanced Weighted K-Nearest Neighbor Algorithm for Indoor Wi-Fi Positioning Systems" @default.
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- W2046128567 doi "https://doi.org/10.4156/ijncm.vol2.issue2.2" @default.
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