{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T13:54:58Z","timestamp":1769349298571,"version":"3.49.0"},"reference-count":29,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T00:00:00Z","timestamp":1555545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004768","name":"Universiti Teknikal Malaysia Melaka","doi-asserted-by":"publisher","award":["PJP\/2018\/FKEKK(3B)\/S01615"],"award-info":[{"award-number":["PJP\/2018\/FKEKK(3B)\/S01615"]}],"id":[{"id":"10.13039\/501100004768","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005417","name":"Universiti Teknologi Malaysia","doi-asserted-by":"publisher","award":["14J64 and 4F966."],"award-info":[{"award-number":["14J64 and 4F966."]}],"id":[{"id":"10.13039\/501100005417","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Indoor localization is a dynamic and exciting research area. WiFi has exhibited a tremendous capability for internal localization since it is extensively used and easily accessible. Facilitating the use of WiFi for this purpose requires fingerprint formation and the implementation of a learning algorithm with the aim of using the fingerprint to determine locations. The most difficult aspect of techniques based on fingerprints is the effect of dynamic environmental changes on fingerprint authentication. With the aim of dealing with this problem, many experts have adopted transfer-learning methods, even though in WiFi indoor localization the dynamic quality of the change in the fingerprint has some cyclic factors that necessitate the use of previous knowledge in various situations. Thus, this paper presents the maximum feature adaptive online sequential extreme learning machine (MFA-OSELM) technique, which uses previous knowledge to handle the cyclic dynamic factors that are brought about by the issue of mobility, which is present in internal environments. This research extends the earlier study of the feature adaptive online sequential extreme learning machine (FA-OSELM). The results of this research demonstrate that MFA-OSELM is superior to FA-OSELM given its capacity to preserve previous data when a person goes back to locations that he\/she had visited earlier. Also, there is always a positive accuracy change when using MFA-OSELM, with the best change achieved being 27% (ranging from eight to 27% and six to 18% for the TampereU and UJIIndoorLoc datasets, respectively), which proves the efficiency of MFA-OSELM in restoring previous knowledge.<\/jats:p>","DOI":"10.3390\/info10040146","type":"journal-article","created":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T11:58:21Z","timestamp":1555588701000},"page":"146","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["MFA-OSELM Algorithm for WiFi-Based Indoor Positioning System"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6746-6011","authenticated-orcid":false,"given":"Ahmed Salih","family":"AL-Khaleefa","sequence":"first","affiliation":[{"name":"Broadband and Networking (BBNET) Research Group, Centre for Telecommunication and Research Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohd Riduan","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Broadband and Networking (BBNET) Research Group, Centre for Telecommunication and Research Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Azmi Awang Md","family":"Isa","sequence":"additional","affiliation":[{"name":"Broadband and Networking (BBNET) Research Group, Centre for Telecommunication and Research Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, Durian Tunggal 76100, Melaka, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ahmed","family":"AL-Saffar","sequence":"additional","affiliation":[{"name":"Faculty of Computer System and Software Engineering, University Malaysia Pahang (UMP), Gambang 26300, Pahang, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mona Riza Mohd","family":"Esa","sequence":"additional","affiliation":[{"name":"Institute of High Voltage and High Current (IVAT), School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia (UTM), Skudai 81310, Johor Bharu, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Reza Firsandaya","family":"Malik","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, Universitas Sriwijaya (UNSRI), Inderalaya, Sumatera Selatan 30151, Indonesia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1109\/MNET.2013.6616116","article-title":"Cloud-enabled wireless body area networks for pervasive healthcare","volume":"27","author":"Wan","year":"2013","journal-title":"IEEE Netw. Mag."},{"key":"ref_2","first-page":"25","article-title":"A Survey on Wireless Indoor Localization from the Device Perspective","volume":"49","author":"Xiao","year":"2016","journal-title":"ACM Comput. Surv. CSUR"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/j.protcy.2014.10.248","article-title":"GuideMe\u2014A Tourist Guide with a Recommender System and Social Interaction","volume":"17","author":"Umanets","year":"2014","journal-title":"Procedia Technol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wang, S., Fidler, S., and Urtasun, R. (2015, January 7\u201313). Lost shopping! Monocular localization in large indoor spaces. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile.","DOI":"10.1109\/ICCV.2015.309"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zou, H., Zhou, Y., Jiang, H., Huang, B., Xie, L., and Spanos, C. (2017, January 19\u201322). Adaptive localization in dynamic indoor environments by transfer kernel learning. Proceedings of the Wireless Communications and Networking Conference (WCNC), San Francisco, CA, USA.","DOI":"10.1109\/WCNC.2017.7925444"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1109\/TMC.2016.2608946","article-title":"Indoor Localization and Automatic Fingerprint Update with Altered AP Signals","volume":"16","author":"He","year":"2017","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_7","first-page":"105","article-title":"Wi-Fi and Motion Sensors Based Indoor Localization Combining ELM and Particle Filter","volume":"Volume 2","author":"Cao","year":"2015","journal-title":"Proceedings of the ELM-2014"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1109\/TKDE.2009.191","article-title":"A Survey on Transfer Learning","volume":"22","author":"Pan","year":"2010","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1007\/s00521-014-1714-x","article-title":"Feature Adaptive Online Sequential Extreme Learning Machine for lifelong indoor localization","volume":"27","author":"Jiang","year":"2016","journal-title":"Neural Comput. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","article-title":"Extreme learning machine: Theory and applications","volume":"70","author":"Huang","year":"2006","journal-title":"Neurocomputing"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Sun, Z., Chen, Y., Qi, J., and Liu, J. (2008, January 11\u201313). Adaptive Localization through Transfer Learning in Indoor Wi-Fi Environment. Proceedings of the 2008 Seventh International Conference on Machine Learning and Applications Adaptive, San Diego, CA, USA.","DOI":"10.1109\/ICMLA.2008.53"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Gu, Y., Liu, J., Chen, Y., and Jiang, X. (2014, January 6\u201311). Constraint Online Sequential Extreme Learning Machine for lifelong indoor localization system. Proceedings of the International Joint Conference on Neural Networks, Beijing, China.","DOI":"10.1109\/IJCNN.2014.6889579"},{"key":"ref_13","unstructured":"Mundo, L.B.D., Ansay, R.L.D., Festin, C.A.M., and Ocampo, R.M. (2011, January 28\u201330). A Comparison of Wireless Fidelity (Wi-Fi) Fingerprinting Techniques. Proceedings of the 2011 International Conference on ICT Convergence (ICTC), Seoul, Korea."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3597","DOI":"10.1109\/TWC.2009.080415","article-title":"UDP identification and error mitigation in ToA-based indoor localization systems using neural network architecture","volume":"8","author":"Heidari","year":"2009","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_15","unstructured":"Huang, G., Zhu, Q., and Siew, C. (2004, January 25\u201329). Extreme Learning Machine: A New Learning Scheme of Feedforward Neural Networks. Proceedings of the 2004 IEEE International Joint Conference on Neural Networks, Budapest, Hungary."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TSMCB.2011.2168604","article-title":"Extreme Learning Machine for Regression and Multiclass Classification","volume":"42","author":"Huang","year":"2012","journal-title":"IEEE Trans. Syst. Man Cybern. Part B Cybern."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1296","DOI":"10.1016\/j.eswa.2006.12.028","article-title":"Introducing a decision tree-based indoor positioning technique","volume":"34","author":"Yim","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_18","unstructured":"Zheng, V.W., Xiang, E.W., Yang, Q., and Shen, D. (2008, January 13\u201317). Transferring localization models over time. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, Chicago, IL, USA."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Koweerawong, C., Wipusitwarakun, K., and Kaemarungsi, K. (2013, January 28\u201330). Indoor localization improvement via adaptive RSS fingerprinting database. Proceedings of the International Conference on Information Networking 2013, Bangkok, Thailand.","DOI":"10.1109\/ICOIN.2013.6496414"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.pmcj.2012.01.001","article-title":"Adaptive radio maps for pattern-matching localization via inter-beacon co-calibration","volume":"8","author":"Lo","year":"2012","journal-title":"Pervasive Mob. Comput."},{"key":"ref_21","first-page":"111","article-title":"An Online Sequential Extreme Learning Machine Approach to WiFi Based Indoor Positioning","volume":"2014","author":"Zou","year":"2014","journal-title":"IEEE World Forum Internet Things"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1109\/TCYB.2015.2399420","article-title":"Robust Extreme Learning Machine With its Application to Indoor Positioning","volume":"46","author":"Lu","year":"2016","journal-title":"IEEE Trans. Cybern."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"6116","DOI":"10.1109\/ACCESS.2018.2791579","article-title":"Pedestrian Dead-Reckoning Indoor Localization Based on OS-ELM","volume":"6","author":"Zhang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"AL-Khaleefa, A.S., Ahmad, M.R., Isa, A.A.M., Esa, M.R.M., AL-Saffar, A., and Hassan, M.H. (2019). Feature Adaptive and Cyclic Dynamic Learning Based on Infinite Term Memory Extreme Learning Machine. Appl. Sci., 9.","DOI":"10.3390\/app9050895"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"54769","DOI":"10.1109\/ACCESS.2018.2870754","article-title":"Infinite-Term Memory Classifier for Wi-Fi Localization Based on Dynamic Wi-Fi Simulator","volume":"6","author":"Ahmad","year":"2018","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1252","DOI":"10.1109\/TWC.2015.2487963","article-title":"A Robust Indoor Positioning System Based on the Procrustes Analysis and Weighted Extreme Learning Machine","volume":"15","author":"Zou","year":"2016","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Han, J., Kamber, M., and Pei, J. (2011). 8\u2014Classification: Basic Concepts. Data Mining: Concepts and Techniques, Elsevier.","DOI":"10.1016\/B978-0-12-381479-1.00009-5"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Torres-Sospedra, J., Montoliu, R., Martinez-Uso, A., Avariento, J.P., Arnau, T.J., Benedito-Bordonau, M., and Huerta, J. (2014, January 27\u201330). UJIIndoorLoc: A new multi-building and multi-floor database for WLAN fingerprint-based indoor localization problems. Proceedings of the 2014 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Busan, Korea.","DOI":"10.1109\/IPIN.2014.7275492"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Lohan, S.E., Torres-Sospedra, J., Lepp\u00e4koski, H., Richter, P., Peng, Z., and Huerta, J. (2017). Wi-Fi crowdsourced fingerprinting dataset for indoor positioning. Data, 2.","DOI":"10.3390\/data2040032"}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/4\/146\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:46:34Z","timestamp":1760186794000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/4\/146"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,18]]},"references-count":29,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["info10040146"],"URL":"https:\/\/doi.org\/10.3390\/info10040146","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,4,18]]}}}