According to the cluster features of similar fingerprints, we proposed a K-Means+ clustering algorithm to achieve fine-grained fingerprint positioning. Due to ...
Experimental results illustrate that our algorithm can get a maximum positioning error less than 5 m, which outperforms other algorithms. Meanwhile, all the ...
Experimental results illustrate that our algorithm can get a maximum positioning error less than 5 m, which outperforms other algorithms. Meanwhile, all the ...
Fingerprint positioning algorithm does not rely on additional hardware overhead, which can utilize the existing infrastructure (e.g., WLAN) to complete the ...
According to clusters distribution feature of corresponding positions of the similar fingerprints, we proposed a K-Means+ clustering algorithm to achieve fine- ...
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Experiments show that the algorithm can effectively deal with the problem of the positioning accuracy of hard clustering. Keywords: Fuzzy Clustering; ...
Missing: Similarity Elimination
Apr 2, 2020 · A positioning algorithm based on the fingerprint database by twice-fuzzy clustering is proposed to obtain the locations of the terminal inside the carriage of ...
Missing: Similarity Indoor
This paper considers the problem of fingerprinting indoor localization based on signal strength measurements RSS. A new approach based on Fuzzy logic has been ...
Missing: Elimination | Show results with:Elimination
Apr 3, 2020 · The purpose is to improve the positioning accuracy without increasing the hardware investment, no matter which devices the users use. The main ...
The KNN algorithm calculates the distance between the fingerprint vector and the fingerprints in the database to determine the k closest fingerprints, and the ...