{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:01:04Z","timestamp":1760241664474,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2018,6,21]],"date-time":"2018-06-21T00:00:00Z","timestamp":1529539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Engineering and Technology Research Center of Guangdong Province for Logistics Supply Chain and Internet of Things","award":["GDDST[2016]176"],"award-info":[{"award-number":["GDDST[2016]176"]}]},{"name":"The Provincial Science and Technology Project in Guangdong Province","award":["2013B090200055"],"award-info":[{"award-number":["2013B090200055"]}]},{"name":"The Key Laboratory of Cloud Computing for Super\u2014integration Cloud Computing in Guangdong Province","award":["610245048129"],"award-info":[{"award-number":["610245048129"]}]},{"name":"The Engineering and Technology Research Center of Guangdong Province for Big Data Intelligent Processing","award":["GDDST[2013]1513-1-11"],"award-info":[{"award-number":["GDDST[2013]1513-1-11"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the rapid development of indoor positioning technology, radio frequency identification (RFID) technology has become the preferred solution due to its advantages of non-line-of-sight, non-contact and rapid identification. However, the accuracy of existing RFID indoor positioning algorithms is easily affected by the tag density and algorithm efficiency, and their environmental robustness is not strong enough. In this paper, we have introduced an RFID positioning algorithm based on the Glowworm Swarm Optimization (GSO) fused with semi-supervised online sequential extreme learning machine (SOS-ELM), which is called the GSOS-ELM algorithm. The GSOS-ELM algorithm automatically adjusts the regularization weights of the SOS-ELM algorithm through the GSO algorithm, so that it can quickly obtain the optimal regularization weights under different initial conditions; at the same time, the semi-supervised characteristics of the GSOS-ELM algorithm can significantly reduce the number of labeled reference tags and reduce the cost of positioning systems. In addition, the online learning phase of the GSOS-ELM algorithm can continuously update the system to perceive changes in the environment and resist the environmental interference. We have carried out experiments to study the influence factors and validate the performance, both the simulation and testbed experiment results show that compared with other algorithms, our proposed GSOS-ELM localization system can achieve more accurate positioning results and has certain adaptability to the changes of the environment.<\/jats:p>","DOI":"10.3390\/s18071995","type":"journal-article","created":{"date-parts":[[2018,6,22]],"date-time":"2018-06-22T02:46:21Z","timestamp":1529635581000},"page":"1995","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["GSOS-ELM: An RFID-Based Indoor Localization System Using GSO Method and Semi-Supervised Online Sequential ELM"],"prefix":"10.3390","volume":"18","author":[{"given":"Fagui","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8290-1803","authenticated-orcid":false,"given":"Dexiang","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,21]]},"reference":[{"key":"ref_1","unstructured":"Hofmann-Wellenhof, B., Lichtenegger, H., and Collins, J. 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