{"id":"https://openalex.org/W3203492870","doi":"https://doi.org/10.1109/tgrs.2021.3112192","title":"Transient Electromagnetic Inversion: An ICDE-Trained Kernel Principal Component OSELM Approach","display_name":"Transient Electromagnetic Inversion: An ICDE-Trained Kernel Principal Component OSELM Approach","publication_year":2021,"publication_date":"2021-09-28","ids":{"openalex":"https://openalex.org/W3203492870","doi":"https://doi.org/10.1109/tgrs.2021.3112192","mag":"3203492870"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2021.3112192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3112192","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5101872959","display_name":"Ruiyou Li","orcid":"https://orcid.org/0000-0002-2213-3352"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiyou Li","raw_affiliation_strings":["School of Electrical Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2213-3352","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101823404","display_name":"Huaiqing Zhang","orcid":"https://orcid.org/0000-0002-2631-4740"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaiqing Zhang","raw_affiliation_strings":["School of Electrical Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2631-4740","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101397419","display_name":"Zhao Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Wu","raw_affiliation_strings":["School of Electrical Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-8574-4396","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069331281","display_name":"Ruiheng Li","orcid":"https://orcid.org/0000-0002-8528-3809"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiheng Li","raw_affiliation_strings":["School of Electrical Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-8528-3809","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158842170"],"apc_list":null,"apc_paid":null,"fwci":0.9554,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80153717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"60","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.991100013256073,"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/T10320","display_name":"Neural Networks and Applications","score":0.9785000085830688,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7528645396232605},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.7419750094413757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6817859411239624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5634713172912598},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5619058609008789},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5443105697631836},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.5037142634391785},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.4976392090320587},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.48404091596603394},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43582460284233093},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4357723295688629},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40962111949920654},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.37721824645996094},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.35612207651138306},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2349839210510254}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7528645396232605},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7419750094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6817859411239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5634713172912598},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5619058609008789},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5443105697631836},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.5037142634391785},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.4976392090320587},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.48404091596603394},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43582460284233093},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4357723295688629},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40962111949920654},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.37721824645996094},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.35612207651138306},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2349839210510254},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2021.3112192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2021.3112192","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6783352553","display_name":null,"funder_award_id":"4210040326","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1964236991","https://openalex.org/W1966691458","https://openalex.org/W1968915050","https://openalex.org/W1971409801","https://openalex.org/W1975479076","https://openalex.org/W1975903543","https://openalex.org/W1977772221","https://openalex.org/W1993002741","https://openalex.org/W1999279042","https://openalex.org/W2014918748","https://openalex.org/W2019123741","https://openalex.org/W2020237187","https://openalex.org/W2020377131","https://openalex.org/W2021826571","https://openalex.org/W2031731345","https://openalex.org/W2048862735","https://openalex.org/W2049211516","https://openalex.org/W2059776567","https://openalex.org/W2062797400","https://openalex.org/W2081229197","https://openalex.org/W2090351291","https://openalex.org/W2102013737","https://openalex.org/W2108064160","https://openalex.org/W2111072639","https://openalex.org/W2122923860","https://openalex.org/W2134530537","https://openalex.org/W2134603844","https://openalex.org/W2138432470","https://openalex.org/W2141695047","https://openalex.org/W2152242052","https://openalex.org/W2155536146","https://openalex.org/W2158054309","https://openalex.org/W2161464081","https://openalex.org/W2168618665","https://openalex.org/W2169976759","https://openalex.org/W2339348901","https://openalex.org/W2351014356","https://openalex.org/W2471081287","https://openalex.org/W2539756129","https://openalex.org/W2550551564","https://openalex.org/W2743138742","https://openalex.org/W2746098316","https://openalex.org/W2772249624","https://openalex.org/W2793359360","https://openalex.org/W2799401390","https://openalex.org/W2894657960","https://openalex.org/W2898291782","https://openalex.org/W2910822716","https://openalex.org/W2914954298","https://openalex.org/W2921711317","https://openalex.org/W2923174252","https://openalex.org/W2962004477","https://openalex.org/W2972700080","https://openalex.org/W2981589591","https://openalex.org/W2984482121","https://openalex.org/W2990450680","https://openalex.org/W2998796746","https://openalex.org/W3004864100","https://openalex.org/W3010857345","https://openalex.org/W3015357525","https://openalex.org/W3023833946","https://openalex.org/W3094709780","https://openalex.org/W3161711397","https://openalex.org/W4240426185","https://openalex.org/W6746596579"],"related_works":["https://openalex.org/W1984421104","https://openalex.org/W2512565647","https://openalex.org/W2001772920","https://openalex.org/W2393746448","https://openalex.org/W2905418897","https://openalex.org/W2534878021","https://openalex.org/W2398887903","https://openalex.org/W1985034083","https://openalex.org/W3093470103","https://openalex.org/W1998640076"],"abstract_inverted_index":{"The":[0,127,143],"traditional":[1],"extreme":[2,40,79],"learning":[3,41,80,93],"machine":[4,42,81],"(ELM)":[5],"inversion":[6,134,144],"of":[7,68,76,98,131,141,146,162,183],"transient":[8],"electromagnetic":[9],"method":[10,52,135],"(TEM)":[11],"based":[12],"on":[13],"random":[14],"initial":[15],"weights":[16],"is":[17,53,62,88,109,121],"known":[18],"to":[19,111,123],"be":[20],"inept":[21],"for":[22,90,180],"its":[23],"low-computational":[24],"efficiency":[25,75,164],"and":[26,71,95,117,129,149,165,168],"poor":[27],"generalization":[28,96],"performance.":[29],"To":[30],"solve":[31],"these":[32],"problems,":[33],"a":[34,84,118,177],"kernel":[35,57],"principal":[36,58],"component":[37,59],"online":[38,77],"sequential":[39,78],"(KPCOSELM)":[43],"trained":[44],"by":[45],"an":[46],"improved":[47],"chaotic":[48,107],"differential":[49],"evolution":[50],"(ICDE)":[51],"proposed.":[54],"An":[55],"additional":[56],"(KPC)":[60],"layer":[61],"used,":[63],"which":[64,175],"reduces":[65],"the":[66,73,92,102,105,113,132,147,154,181],"dimension":[67],"TEM":[69,173,187],"data":[70],"enhances":[72],"computational":[74,163],"(OSELM).":[82],"Moreover,":[83],"novel":[85],"ICDE":[86],"algorithm":[87],"presented":[89],"improving":[91],"ability":[94],"performance":[97,171],"OSELM":[99],"inversion.":[100,188],"In":[101],"proposed":[103,133,155],"ICDE,":[104],"tent":[106],"sequence":[108],"adopted":[110],"enhance":[112],"global":[114],"exploitation":[115],"ability,":[116],"constraint":[119],"factor":[120],"added":[122],"ensure":[124],"better":[125],"convergence.":[126],"feasibility":[128],"effectiveness":[130],"are":[136],"evaluated":[137],"via":[138],"four":[139],"groups":[140],"experiments.":[142],"results":[145],"synthetic":[148],"field":[150],"examples":[151],"show":[152],"that":[153],"approach":[156],"outperformed":[157],"other":[158],"methods":[159],"in":[160,172,186],"terms":[161],"prediction":[166],"accuracy,":[167],"realized":[169],"satisfactory":[170],"inversion,":[174],"provides":[176],"new":[178],"strategy":[179],"application":[182],"neural":[184],"networks":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
