{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,14]],"date-time":"2026-08-14T16:07:41Z","timestamp":1786723661686,"version":"build-2736575974"},"reference-count":23,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T00:00:00Z","timestamp":1681344000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["61741303"],"award-info":[{"award-number":["61741303"]}]},{"name":"National Natural Science Foundation of China","award":["2022GXZDSY003"],"award-info":[{"award-number":["2022GXZDSY003"]}]},{"name":"National Natural Science Foundation of China","award":["19-185-10-08"],"award-info":[{"award-number":["19-185-10-08"]}]},{"name":"National Natural Science Foundation of China","award":["2023"],"award-info":[{"award-number":["2023"]}]},{"name":"Key Laboratory of AI and Information Processing (Hechi University)","award":["61741303"],"award-info":[{"award-number":["61741303"]}]},{"name":"Key Laboratory of AI and Information Processing (Hechi University)","award":["2022GXZDSY003"],"award-info":[{"award-number":["2022GXZDSY003"]}]},{"name":"Key Laboratory of AI and Information Processing (Hechi University)","award":["19-185-10-08"],"award-info":[{"award-number":["19-185-10-08"]}]},{"name":"Key Laboratory of AI and Information Processing (Hechi University)","award":["2023"],"award-info":[{"award-number":["2023"]}]},{"name":"Education Department of Guangxi Zhuang Autonomous Region","award":["61741303"],"award-info":[{"award-number":["61741303"]}]},{"name":"Education Department of Guangxi Zhuang Autonomous Region","award":["2022GXZDSY003"],"award-info":[{"award-number":["2022GXZDSY003"]}]},{"name":"Education Department of Guangxi Zhuang Autonomous Region","award":["19-185-10-08"],"award-info":[{"award-number":["19-185-10-08"]}]},{"name":"Education Department of Guangxi Zhuang Autonomous Region","award":["2023"],"award-info":[{"award-number":["2023"]}]},{"name":"Key Laboratory of Spatial Information and Geomatics (Guilin University of Technology)","award":["61741303"],"award-info":[{"award-number":["61741303"]}]},{"name":"Key Laboratory of Spatial Information and Geomatics (Guilin University of Technology)","award":["2022GXZDSY003"],"award-info":[{"award-number":["2022GXZDSY003"]}]},{"name":"Key Laboratory of Spatial Information and Geomatics (Guilin University of Technology)","award":["19-185-10-08"],"award-info":[{"award-number":["19-185-10-08"]}]},{"name":"Key Laboratory of Spatial Information and Geomatics (Guilin University of Technology)","award":["2023"],"award-info":[{"award-number":["2023"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["61741303"],"award-info":[{"award-number":["61741303"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["2022GXZDSY003"],"award-info":[{"award-number":["2022GXZDSY003"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["19-185-10-08"],"award-info":[{"award-number":["19-185-10-08"]}]},{"name":"Innovation Project of Guangxi Graduate Education","award":["2023"],"award-info":[{"award-number":["2023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Considering the low indoor positioning accuracy and poor positioning stability of traditional machine-learning algorithms, an indoor-fingerprint-positioning algorithm based on weighted k-nearest neighbors (WKNN) and extreme gradient boosting (XGBoost) was proposed in this study. Firstly, the outliers in the dataset of established fingerprints were removed by Gaussian filtering to enhance the data reliability. Secondly, the sample set was divided into a training set and a test set, followed by modeling using the XGBoost algorithm with the received signal strength data at each access point (AP) in the training set as the feature, and the coordinates as the label. Meanwhile, such parameters as the learning rate in the XGBoost algorithm were dynamically adjusted via the genetic algorithm (GA), and the optimal value was searched based on a fitness function. Then, the nearest neighbor set searched by the WKNN algorithm was introduced into the XGBoost model, and the final predicted coordinates were acquired after weighted fusion. As indicated in the experimental results, the average positioning error of the proposed algorithm is 1.22 m, which is 20.26\u201345.58% lower than that of traditional indoor positioning algorithms. In addition, the cumulative distribution function (CDF) curve can converge faster, reflecting better positioning performance.<\/jats:p>","DOI":"10.3390\/s23083952","type":"journal-article","created":{"date-parts":[[2023,4,14]],"date-time":"2023-04-14T02:03:38Z","timestamp":1681437818000},"page":"3952","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["An Indoor Fingerprint Positioning Algorithm Based on WKNN and Improved XGBoost"],"prefix":"10.3390","volume":"23","author":[{"given":"Haizhao","family":"Lu","sequence":"first","affiliation":[{"name":"College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3740-0377","authenticated-orcid":false,"given":"Lieping","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyuan","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shenglan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shoufeng","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, Guilin University of Technology AT Nanning, Nanning 532100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huihao","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianchu","family":"Zou","sequence":"additional","affiliation":[{"name":"Key Laboratory of AI and Information Processing, Education Department of Guangxi Zhuang Autonomous Region, Hechi University, Yizhou 546300, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sarcevic, P., Csik, D., and Odry, A. 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