{"id":"https://openalex.org/W4415968960","doi":"https://doi.org/10.1109/iecon58223.2025.11221395","title":"Soft Sensing of Ocean Current Velocity Profiles Based on Stratified Hybrid Convolutional Network","display_name":"Soft Sensing of Ocean Current Velocity Profiles Based on Stratified Hybrid Convolutional Network","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W4415968960","doi":"https://doi.org/10.1109/iecon58223.2025.11221395"},"language":null,"primary_location":{"id":"doi:10.1109/iecon58223.2025.11221395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-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":null,"display_name":"Haoxian Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoxian Wen","raw_affiliation_strings":["China University of Geosciences,School of Automation,Wuhan,China,430074"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Automation,Wuhan,China,430074","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017920898","display_name":"Sheng Du","orcid":"https://orcid.org/0000-0001-8396-7388"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sheng Du","raw_affiliation_strings":["China University of Geosciences,School of Automation,Wuhan,China,430074"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Automation,Wuhan,China,430074","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090328003","display_name":"Chengda Lu","orcid":"https://orcid.org/0000-0002-9452-4053"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengda Lu","raw_affiliation_strings":["China University of Geosciences,School of Automation,Wuhan,China,430074"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Automation,Wuhan,China,430074","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079554980","display_name":"Yawu Wang","orcid":"https://orcid.org/0000-0001-7027-2851"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawu Wang","raw_affiliation_strings":["China University of Geosciences,School of Automation,Wuhan,China,430074"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Automation,Wuhan,China,430074","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074710425","display_name":"Min Wu","orcid":"https://orcid.org/0000-0002-0668-8315"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Wu","raw_affiliation_strings":["China University of Geosciences,School of Automation,Wuhan,China,430074"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China University of Geosciences,School of Automation,Wuhan,China,430074","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27964223,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.5278000235557556,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10255","display_name":"Oceanographic and Atmospheric Processes","score":0.5278000235557556,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.13109999895095825,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.1225999966263771,"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/overfitting","display_name":"Overfitting","score":0.6036999821662903},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.574400007724762},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.5041000247001648},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.4415999948978424},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.43939998745918274},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42419999837875366},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.40849998593330383},{"id":"https://openalex.org/keywords/current","display_name":"Current (fluid)","score":0.40849998593330383},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.3968999981880188}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6036999821662903},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.574400007724762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5533999800682068},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.5041000247001648},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.4415999948978424},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42419999837875366},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.40849998593330383},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.3968999981880188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3880999982357025},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.37720000743865967},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37040001153945923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3603000044822693},{"id":"https://openalex.org/C187599188","wikidata":"https://www.wikidata.org/wiki/Q129558","display_name":"Ocean current","level":2,"score":0.35269999504089355},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C142757262","wikidata":"https://www.wikidata.org/wiki/Q76436","display_name":"Doppler effect","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.328000009059906},{"id":"https://openalex.org/C2779365185","wikidata":"https://www.wikidata.org/wiki/Q624383","display_name":"Acoustic Doppler current profiler","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29679998755455017},{"id":"https://openalex.org/C2776248883","wikidata":"https://www.wikidata.org/wiki/Q17154087","display_name":"Ocean observations","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C192943249","wikidata":"https://www.wikidata.org/wiki/Q1893382","display_name":"Stratification (seeds)","level":5,"score":0.2721000015735626},{"id":"https://openalex.org/C2778559676","wikidata":"https://www.wikidata.org/wiki/Q1334213","display_name":"Doppler radar","level":3,"score":0.26499998569488525},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.2547999918460846},{"id":"https://openalex.org/C197424946","wikidata":"https://www.wikidata.org/wiki/Q1165717","display_name":"Waveform","level":3,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iecon58223.2025.11221395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iecon58223.2025.11221395","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IECON 2025 \u2013 51st Annual Conference of the IEEE Industrial Electronics Society","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320328899","display_name":"China University of Geosciences","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2592632110","https://openalex.org/W3158937244","https://openalex.org/W4365139425","https://openalex.org/W4383220325","https://openalex.org/W4384197226","https://openalex.org/W4387528601","https://openalex.org/W4391914030","https://openalex.org/W4393110967","https://openalex.org/W4402262259","https://openalex.org/W4408858321","https://openalex.org/W4409262283"],"related_works":[],"abstract_inverted_index":{"Measurement":[0],"of":[1,72,142],"ocean":[2,60,73,143],"current":[3,61,144],"velocity":[4,62,145],"profiles":[5],"is":[6],"critical":[7],"for":[8,58,124,139],"marine":[9],"operations,":[10],"yet":[11],"traditional":[12],"methods":[13],"such":[14],"as":[15],"Acoustic":[16],"Doppler":[17],"Current":[18],"Profilers":[19],"face":[20],"limitations":[21],"in":[22],"cost,":[23],"resolution,":[24],"and":[25,82,97,113],"penetration":[26],"depth.":[27],"Existing":[28],"inversion":[29,141],"techniques":[30],"often":[31],"rely":[32],"on":[33,79],"idealized":[34],"assumptions":[35],"limiting":[36],"their":[37,83],"practical":[38,137],"applicability.":[39],"To":[40],"address":[41],"these":[42],"challenges,":[43],"this":[44],"paper":[45],"proposes":[46],"stratified":[47],"hybrid":[48,104],"convolutional":[49],"network,":[50],"a":[51,68,136],"novel":[52],"deep":[53],"learning-based":[54],"soft":[55],"sensing":[56],"method":[57,66,134],"reconstructing":[59],"profiles.":[63,146],"The":[64],"proposed":[65],"leverages":[67],"physically":[69],"guided":[70],"stratification":[71],"currents":[74],"into":[75],"distinct":[76],"layers":[77],"based":[78],"temperature-salinity-density":[80],"correlations":[81],"driving":[84],"mechanisms.":[85],"An":[86],"adaptive":[87],"feature":[88,114],"selection":[89],"algorithm":[90],"mitigates":[91],"overfitting":[92],"by":[93,121],"filtering":[94],"redundant":[95],"inputs":[96],"aligning":[98],"features":[99],"with":[100],"layer-specific":[101],"dynamics.":[102],"A":[103],"neural":[105],"network":[106],"architecture":[107],"combines":[108],"two-dimensional":[109],"convolutions":[110],"along":[111],"depth":[112],"dimensions":[115],"to":[116],"capture":[117],"nonlinear":[118,126],"relationships,":[119],"followed":[120],"multi-layer":[122],"perceptrons":[123],"high-dimensional":[125],"mapping.":[127],"Experimental":[128],"results":[129],"demonstrate":[130],"superior":[131],"performance.":[132],"This":[133],"provides":[135],"solution":[138],"the":[140]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-06T00:00:00"}