Adaptive Multi-Type Fingerprint Indoor Positioning and Localization Method Based on Multi-Task Learning and Weight Coefficients <i>K</i>-Nearest Neighbor

Adaptive Multi-Type Fingerprint Indoor Positioning and Localization Method Based on Multi-Task Learning and Weight Coefficients <i>K</i>-Nearest Neighbor

The complex indoor environment makes the use of received fingerprints unreliable as an indoor positioning and localization method based on fingerprint data. This paper proposes an adaptive multi-type fingerprint indoor positioning and localization method based on multi-task learning (MTL) and Weight...

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Bibliographic Details
Main Authors:	Zhengwu Yuan, Xupeng Zha, Xiaojian Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2020-09-01
Series:	Sensors
Subjects:	multi-type fingerprints indoor positioning and localization multi-task learning weight coefficients <i>K</i>-Nearest neighbor
Online Access:	https://www.mdpi.com/1424-8220/20/18/5416

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