{"id":"https://openalex.org/W4391468540","doi":"https://doi.org/10.1109/wcsp58612.2023.10404687","title":"Deep Neural Network Based Matched-Field Geoacoustic Inversion","display_name":"Deep Neural Network Based Matched-Field Geoacoustic Inversion","publication_year":2023,"publication_date":"2023-11-02","ids":{"openalex":"https://openalex.org/W4391468540","doi":"https://doi.org/10.1109/wcsp58612.2023.10404687"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp58612.2023.10404687","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcsp58612.2023.10404687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Wireless Communications and Signal Processing (WCSP)","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":"https://openalex.org/A5042617810","display_name":"Ruopeng Xu","orcid":"https://orcid.org/0009-0008-9028-812X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruopeng Xu","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006705527","display_name":"Hongnan Chen","orcid":"https://orcid.org/0000-0002-9136-1420"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongnan Chen","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100458341","display_name":"Ting Zhang","orcid":"https://orcid.org/0000-0002-9440-3219"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]},{"id":"https://openalex.org/I4210141176","display_name":"Communication University of Zhejiang","ror":"https://ror.org/04t7gxr16","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210141176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Zhang","raw_affiliation_strings":["Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Hangzhou, China","College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Information Science and Electronic Engineering,Hangzhou,China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Hangzhou, China","institution_ids":["https://openalex.org/I4210141176"]},{"raw_affiliation_string":"College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042617810"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04959473,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"676","last_page":"682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9998999834060669,"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/T11698","display_name":"Underwater Acoustics Research","score":0.9998999834060669,"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/T11609","display_name":"Geophysical Methods and Applications","score":0.9995999932289124,"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"}},{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.7776590585708618},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6963383555412292},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5774513483047485},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.556182324886322},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.5091902613639832},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.45078176259994507},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.4159359335899353},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41429728269577026},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.413392037153244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33791837096214294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15256401896476746},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14675244688987732}],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7776590585708618},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6963383555412292},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5774513483047485},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.556182324886322},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.5091902613639832},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.45078176259994507},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.4159359335899353},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41429728269577026},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.413392037153244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33791837096214294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15256401896476746},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14675244688987732},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp58612.2023.10404687","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/wcsp58612.2023.10404687","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.5299999713897705,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1930739603","https://openalex.org/W2030004508","https://openalex.org/W2166212328","https://openalex.org/W2344794235","https://openalex.org/W2560674852","https://openalex.org/W2606365144","https://openalex.org/W2969976430","https://openalex.org/W2979589711","https://openalex.org/W3158102650","https://openalex.org/W3183468528","https://openalex.org/W6637242042"],"related_works":["https://openalex.org/W3106461837","https://openalex.org/W4283700523","https://openalex.org/W3168182983","https://openalex.org/W4387079005","https://openalex.org/W4321472004","https://openalex.org/W4221166418","https://openalex.org/W3117893869","https://openalex.org/W2968265130","https://openalex.org/W2973085194","https://openalex.org/W4401858220"],"abstract_inverted_index":{"Acoustic":[0],"field":[1,24,29],"inversion":[2,18,79,107,150],"offers":[3],"an":[4,32],"efficient":[5],"approach":[6,128],"for":[7,48],"estimating":[8],"geoacoustic":[9,14],"parameters":[10],"and":[11,54,72,159],"acquiring":[12],"valuable":[13],"characteristics.":[15],"The":[16],"matched-field":[17,78,124,149],"technique":[19,46],"aligns":[20],"the":[21,45,49,63,67,84,122,131],"measured":[22,160],"acoustic":[23,28,33,52,85],"with":[25,156],"a":[26,41,90,97,116],"copy":[27],"generated":[30],"by":[31],"propagation":[34,86],"model.":[35],"By":[36],"employing":[37],"optimization":[38,70],"algorithms":[39],"in":[40,77,89],"high-dimensional":[42],"parameter":[43,64],"space,":[44],"searches":[47],"best":[50],"matching":[51],"parameters,":[53],"Bayesian":[55],"theory":[56],"is":[57],"then":[58],"applied":[59],"to":[60,162],"further":[61],"determine":[62],"uncertainties.":[65],"However,":[66],"traditional":[68],"global":[69],"process":[71,120],"posterior":[73],"probability":[74],"density":[75],"sampling":[76],"require":[80],"multiple":[81],"calls":[82],"of":[83,133],"model,":[87],"resulting":[88],"considerable":[91],"computational":[92],"time":[93,102,137],"cost.":[94],"Although":[95],"using":[96],"surrogate":[98],"model":[99],"can":[100],"enhance":[101],"efficiency,":[103],"it":[104],"often":[105],"compromises":[106],"accuracy.":[108,141],"To":[109],"address":[110],"this":[111,143],"challenge,":[112],"we":[113,145],"propose":[114],"intergrating":[115],"deep":[117],"learning-based":[118],"pre-screening":[119],"into":[121],"conventional":[123],"inversion.":[125],"This":[126],"innovative":[127],"significantly":[129],"reduces":[130],"number":[132],"calls,":[134],"thereby":[135],"reducing":[136],"costs":[138],"without":[139],"sacrificing":[140],"In":[142],"paper,":[144],"conduct":[146],"experiments":[147],"on":[148,152],"based":[151],"Deep":[153],"Neural":[154],"Networks":[155],"simulated":[157],"data":[158,161],"validate":[163],"its":[164],"efficacy.":[165]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}