In order to address this problem, we propose a dynamic KNN algorithm that can adjust the value of K dynamically to offset noises of different levels. The value ...
Abstract—K-nearest neighbor (KNN) fingerprint positioning is a promising solution for WLAN-based indoor positioning that has received much attention over ...
This work proposes a dynamic KNN algorithm that can adjust the value of K dynamically to offset noises of different levels based on the WiFi signals ...
In order to address this problem, we propose a dynamic KNN algorithm that can adjust the value of K dynamically to offset noises of different levels. The value ...
Jul 4, 2023 · Jiusong Hu, Hongli Liu, Dawei Liu: Toward a Dynamic K in K-Nearest Neighbor Fingerprint Indoor Positioning. IRI 2018: 308-314.
Dive into the research topics of 'Toward A Dynamic K in K-nearest neighbor fingerprint indoor positioning'. Together they form a unique fingerprint. Sort by ...
Nov 30, 2023 · In this paper, for the first time, we propose a domain-specific concept of interpretability, based on identifying the access points that are most relevant to a ...
People also ask
What is the K value in K nearest neighbor?
What is K nearest neighbor feature matching?
What is K nearest neighbor algorithm localization?
What are outliers in K nearest neighbors?
Jun 17, 2022 · Fingerprinting methods explore the mapping between positions and unique features such as RSS from different WiFi access points or the CSI and ...
An enhanced K-Nearest Neighbor algorithm for indoor positioning ...
www.researchgate.net › ... › WLAN
In this paper we propose a robust fingerprint method for localization based on the traditional K-Nearest Neighbor (KNN) method. Instead of considering a fixed ...
Apr 13, 2023 · An indoor-fingerprint-positioning algorithm based on weighted k-nearest neighbors (WKNN) and extreme gradient boosting (XGBoost) was proposed in this study.
Missing: Toward | Show results with:Toward