{"id":"https://openalex.org/W3158380703","doi":"https://doi.org/10.1109/tim.2021.3072699","title":"Indoor Geomagnetic Positioning Using the Enhanced Genetic Algorithm-Based Extreme Learning Machine","display_name":"Indoor Geomagnetic Positioning Using the Enhanced Genetic Algorithm-Based Extreme Learning Machine","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3158380703","doi":"https://doi.org/10.1109/tim.2021.3072699","mag":"3158380703"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3072699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3072699","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037893752","display_name":"Meng Sun","orcid":"https://orcid.org/0000-0002-9158-3787"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Sun","raw_affiliation_strings":["Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018788326","display_name":"Yunjia Wang","orcid":"https://orcid.org/0000-0002-1903-242X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjia Wang","raw_affiliation_strings":["Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070723676","display_name":"Shenglei Xu","orcid":"https://orcid.org/0000-0001-7141-3580"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenglei Xu","raw_affiliation_strings":["Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083099906","display_name":"Hongchao Yang","orcid":"https://orcid.org/0000-0002-0848-8632"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongchao Yang","raw_affiliation_strings":["Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100686951","display_name":"Kewei Zhang","orcid":"https://orcid.org/0000-0001-6377-1900"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kewei Zhang","raw_affiliation_strings":["Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Land Environment and Disaster Monitoring, MNR, School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5037893752"],"corresponding_institution_ids":["https://openalex.org/I25757504"],"apc_list":null,"apc_paid":null,"fwci":3.6431,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.93542889,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.9776999950408936,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/earths-magnetic-field","display_name":"Earth's magnetic field","score":0.6366271376609802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5382039546966553},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5320939421653748},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.4310910701751709},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37420517206192017},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36038243770599365},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25561270117759705},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.16848132014274597},{"id":"https://openalex.org/keywords/magnetic-field","display_name":"Magnetic field","score":0.14584314823150635},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13958615064620972}],"concepts":[{"id":"https://openalex.org/C199635899","wikidata":"https://www.wikidata.org/wiki/Q6500960","display_name":"Earth's magnetic field","level":3,"score":0.6366271376609802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5382039546966553},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5320939421653748},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.4310910701751709},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37420517206192017},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36038243770599365},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25561270117759705},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.16848132014274597},{"id":"https://openalex.org/C115260700","wikidata":"https://www.wikidata.org/wiki/Q11408","display_name":"Magnetic field","level":2,"score":0.14584314823150635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13958615064620972},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3072699","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3072699","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G7795442269","display_name":null,"funder_award_id":"2016YFB0502102","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W1013072532","https://openalex.org/W1026239909","https://openalex.org/W1567102157","https://openalex.org/W1787544972","https://openalex.org/W1965895201","https://openalex.org/W1971760893","https://openalex.org/W1991295181","https://openalex.org/W2018496305","https://openalex.org/W2022637272","https://openalex.org/W2068546584","https://openalex.org/W2079251198","https://openalex.org/W2111072639","https://openalex.org/W2123876002","https://openalex.org/W2146661052","https://openalex.org/W2147243899","https://openalex.org/W2158054309","https://openalex.org/W2169462560","https://openalex.org/W2170102584","https://openalex.org/W2260859552","https://openalex.org/W2278572312","https://openalex.org/W2319208717","https://openalex.org/W2336558231","https://openalex.org/W2343889204","https://openalex.org/W2461937780","https://openalex.org/W2739513368","https://openalex.org/W2763643916","https://openalex.org/W2775147633","https://openalex.org/W2781901404","https://openalex.org/W2792091676","https://openalex.org/W2796039375","https://openalex.org/W2799542324","https://openalex.org/W2804830978","https://openalex.org/W2884289020","https://openalex.org/W2886678529","https://openalex.org/W2888342233","https://openalex.org/W2902997965","https://openalex.org/W2903577397","https://openalex.org/W2903653767","https://openalex.org/W2904250082","https://openalex.org/W2907523925","https://openalex.org/W2920745458","https://openalex.org/W2945504666","https://openalex.org/W2956107375","https://openalex.org/W2956936418","https://openalex.org/W2977364979","https://openalex.org/W2980624823","https://openalex.org/W2992379457","https://openalex.org/W3000568877","https://openalex.org/W3008373994","https://openalex.org/W3015022426","https://openalex.org/W3017181332","https://openalex.org/W3124420883","https://openalex.org/W4211023471","https://openalex.org/W6626639484","https://openalex.org/W6654920567","https://openalex.org/W6741831385"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W2743832667","https://openalex.org/W1584764049"],"abstract_inverted_index":{"Indoor":[0],"positioning":[1,57],"using":[2,98],"the":[3,13,17,31,60,67,84,90,121,130,156,162],"geomagnetic":[4,42,56],"field":[5],"has":[6,140],"become":[7],"a":[8,51],"popular":[9,157],"technique":[10],"because":[11],"of":[12,155],"infrastructure-free":[14],"characteristic":[15],"and":[16,38,53,108,139,167],"ubiquitous":[18],"magnetic":[19],"signals":[20],"in":[21],"indoor":[22],"environments.":[23],"Geomagnetic":[24],"intensity":[25],"will":[26],"generate":[27],"fluctuations":[28],"due":[29],"to":[30,82,119],"factors":[32],"such":[33,160],"as":[34,161],"device":[35],"heterogeneity,":[36],"dates,":[37],"electronic":[39],"facilities.":[40],"Stable":[41],"data":[43],"are":[44,105,117],"essential":[45],"for":[46,89,112],"high-precision":[47],"positioning.":[48],"To":[49],"find":[50,83],"robust":[52],"low":[54],"time-consuming":[55],"model":[58,133,148],"(GPM),":[59],"extreme":[61],"learning":[62,158],"machine":[63],"(ELM)":[64],"optimized":[65],"by":[66,95],"enhanced":[68],"genetic":[69],"algorithm":[70],"(EGA)":[71],"is":[72,80,150],"constructed.":[73],"The":[74,125,147],"EGA":[75],"with":[76],"three":[77],"optimization":[78],"strategies":[79],"designed":[81],"best":[85],"initial":[86],"parameters":[87],"solutions":[88],"ELM.":[91],"Magnetic":[92],"patterns":[93],"collected":[94],"different":[96,99,103,144],"participants":[97],"mobile":[100],"phones":[101],"on":[102],"dates":[104],"extracted":[106],"characteristics":[107],"divided":[109],"into":[110],"segments":[111],"ELM":[113,132],"training.":[114],"Extensive":[115],"experiments":[116],"conducted":[118],"evaluate":[120],"proposed":[122],"model\u2019s":[123],"performance.":[124],"experimental":[126],"results":[127],"demonstrate":[128],"that":[129,154],"EGA-based":[131],"can":[134],"achieve":[135],"meter-level":[136],"location":[137],"accuracy":[138],"good":[141],"robustness":[142],"under":[143],"testing":[145],"conditions.":[146],"construction":[149],"much":[151],"faster":[152],"than":[153],"algorithms,":[159],"convolutional":[163],"neural":[164],"networks":[165],"(CNNs)":[166],"backpropagation":[168],"(BP)":[169],"networks.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
