{"id":"https://openalex.org/W4327521042","doi":"https://doi.org/10.1145/3573428.3573505","title":"Study on transfer learning of shield tunneling parameters based on LSTM model","display_name":"Study on transfer learning of shield tunneling parameters based on LSTM model","publication_year":2022,"publication_date":"2022-10-21","ids":{"openalex":"https://openalex.org/W4327521042","doi":"https://doi.org/10.1145/3573428.3573505"},"language":"en","primary_location":{"id":"doi:10.1145/3573428.3573505","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573428.3573505","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering","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/A5000895758","display_name":"Huanhuan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huanhuan Liu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085993318","display_name":"Shanglin Liu","orcid":"https://orcid.org/0000-0002-3630-0334"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanglin Liu","raw_affiliation_strings":["School of Mechanical Engineering, Tianjin University, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078498439","display_name":"Qian Zhang","orcid":"https://orcid.org/0000-0001-7210-654X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Tianjin University, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100704816","display_name":"Wei Guo","orcid":"https://orcid.org/0000-0002-7804-0032"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Guo","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000895758"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18228952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"443","last_page":"448"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T12482","display_name":"Tunneling and Rock Mechanics","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T11046","display_name":"Geotechnical Engineering and Analysis","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10161","display_name":"Rock Mechanics and Modeling","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/computer-science","display_name":"Computer science","score":0.7078592777252197},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.647956132888794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5847707390785217},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.474122554063797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4413593113422394},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4302177131175995},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4199259877204895},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.41422462463378906},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.08986178040504456}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7078592777252197},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.647956132888794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5847707390785217},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.474122554063797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4413593113422394},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4302177131175995},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4199259877204895},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.41422462463378906},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.08986178040504456},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3573428.3573505","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3573428.3573505","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 6th International Conference on Electronic Information Technology and Computer Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2136848157","https://openalex.org/W2912500072","https://openalex.org/W2950705418","https://openalex.org/W2998115938","https://openalex.org/W3010738077","https://openalex.org/W3041133507","https://openalex.org/W3116862438","https://openalex.org/W3195996253","https://openalex.org/W3200813202","https://openalex.org/W3207309133"],"related_works":["https://openalex.org/W4308262314","https://openalex.org/W4281382123","https://openalex.org/W4213299466","https://openalex.org/W2960456850","https://openalex.org/W4318834068","https://openalex.org/W4281645081","https://openalex.org/W4318957922","https://openalex.org/W4294306704","https://openalex.org/W2946016983","https://openalex.org/W4313050734"],"abstract_inverted_index":{"During":[0,118],"the":[1,4,8,11,40,45,74,83,92,96,101,107,115,121,124,131,144,151,159,163,178,182,190,193,197],"excavation":[2],"of":[3,10,25,58,77,85,123,165,184,192],"shield":[5,15,78],"tunneling":[6,16,79],"machine,":[7],"performance":[9],"existing":[12],"methods":[13],"for":[14],"machine":[17,80],"parameter":[18,81],"prediction":[19,32,75,97,116,194],"often":[20],"require":[21],"a":[22,29,56],"large":[23],"amount":[24,84],"data":[26,42,86,176,198],"to":[27,50,72,105,158],"train":[28],"relatively":[30],"accurate":[31],"model,":[33],"which":[34],"is":[35,48,68,87,200],"in":[36],"great":[37],"contradiction":[38],"with":[39,114,147,174],"limited":[41],"collected":[43],"when":[44,82,196],"subway":[46,133],"line":[47],"beginning":[49],"be":[51],"constructed.":[52],"In":[53],"this":[54],"paper,":[55],"set":[57],"transfer":[59,119,125,137,153,166,185],"learning":[60,138,154,167,186],"model":[61,90,126,155,172,195],"based":[62],"on":[63,130],"long":[64],"short-term":[65],"memory":[66],"(LSTM)":[67],"designed":[69],"and":[70,99,150,168],"built":[71],"improve":[73,189],"process":[76],"small.":[88,201],"The":[89,135],"selects":[91],"cutterhead":[93],"torque":[94],"as":[95],"target":[98],"uses":[100],"Pearson":[102],"coefficient":[103],"method":[104],"filter":[106],"input":[108],"features":[109],"that":[110,181],"are":[111],"highly":[112],"correlated":[113],"target.":[117],"learning,":[120],"pre-training":[122,145],"was":[127,140,156],"first":[128],"performed":[129],"Beijing":[132],"dataset.":[134],"best":[136],"scheme":[139],"selected":[141],"by":[142],"freezing":[143],"models":[146],"different":[148,175],"layers":[149],"optimal":[152],"transferred":[157],"Tianjin":[160],"Metro.":[161],"Comparing":[162],"results":[164,179],"directly":[169],"using":[170],"LSTM":[171],"training":[173],"volumes,":[177],"show":[180],"use":[183],"can":[187],"effectively":[188],"accuracy":[191],"volume":[199]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}