{"id":"https://openalex.org/W4390071648","doi":"https://doi.org/10.1109/idaacs58523.2023.10348906","title":"Analysis and Forecast of Subway Construction Cost Based on Bayesian Network","display_name":"Analysis and Forecast of Subway Construction Cost Based on Bayesian Network","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4390071648","doi":"https://doi.org/10.1109/idaacs58523.2023.10348906"},"language":"en","primary_location":{"id":"doi:10.1109/idaacs58523.2023.10348906","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/idaacs58523.2023.10348906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5017090099","display_name":"Feng Guo","orcid":"https://orcid.org/0000-0001-8794-5709"},"institutions":[{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Guo","raw_affiliation_strings":["China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008","institution_ids":["https://openalex.org/I4210135994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111098204","display_name":"Donghui Niu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghui Niu","raw_affiliation_strings":["China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008","institution_ids":["https://openalex.org/I4210135994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103164915","display_name":"Guoling Zhang","orcid":"https://orcid.org/0000-0003-3039-1850"},"institutions":[{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoling Zhang","raw_affiliation_strings":["China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008","institution_ids":["https://openalex.org/I4210135994"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054712480","display_name":"Na Hou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135994","display_name":"China Railway Group (China)","ror":"https://ror.org/03za3eq42","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210135994"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Na Hou","raw_affiliation_strings":["China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Railway Seventh Bureau Group Electrical Engineering Co., Ltd,Zhengzhou,China,450008","institution_ids":["https://openalex.org/I4210135994"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065438358","display_name":"Zhengbing Hu","orcid":"https://orcid.org/0000-0002-6140-3351"},"institutions":[{"id":"https://openalex.org/I202483615","display_name":"National Technical University of Ukraine \u201cIgor Sikorsky Kyiv Polytechnic Institute\u201d","ror":"https://ror.org/00syn5v21","country_code":"UA","type":"education","lineage":["https://openalex.org/I202483615"]}],"countries":["UA"],"is_corresponding":false,"raw_author_name":"Zhengbing Hu","raw_affiliation_strings":["National Technical University of Ukraine &#x201C;Igor Sikorsky Kyiv Polytechnic Institute&#x201D;,Kyiv,Ukraine"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Ukraine &#x201C;Igor Sikorsky Kyiv Polytechnic Institute&#x201D;,Kyiv,Ukraine","institution_ids":["https://openalex.org/I202483615"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"519","last_page":"524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9588000178337097,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.9588000178337097,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.944100022315979,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.6190939545631409},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6072513461112976},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.597943127155304},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5808165073394775},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.546256422996521},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5102713108062744},{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.501579999923706},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.49912023544311523},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.47333934903144836},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42278924584388733},{"id":"https://openalex.org/keywords/engineering-design-process","display_name":"Engineering design process","score":0.41472870111465454},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.28725579380989075},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27510878443717957},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2556164860725403}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6190939545631409},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6072513461112976},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.597943127155304},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5808165073394775},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.546256422996521},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5102713108062744},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.501579999923706},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.49912023544311523},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.47333934903144836},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42278924584388733},{"id":"https://openalex.org/C34972735","wikidata":"https://www.wikidata.org/wiki/Q2920267","display_name":"Engineering design process","level":2,"score":0.41472870111465454},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28725579380989075},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27510878443717957},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2556164860725403},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idaacs58523.2023.10348906","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/idaacs58523.2023.10348906","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2032778106","https://openalex.org/W2078340289","https://openalex.org/W2516292694","https://openalex.org/W2921799477","https://openalex.org/W3016531978","https://openalex.org/W3017072194","https://openalex.org/W3021873562","https://openalex.org/W3109470735","https://openalex.org/W3112874927","https://openalex.org/W3126698076","https://openalex.org/W4231878650","https://openalex.org/W4364321326"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W3128072696","https://openalex.org/W2578973671","https://openalex.org/W2215058820","https://openalex.org/W2097663773","https://openalex.org/W1602184117","https://openalex.org/W2413421635","https://openalex.org/W2511198839","https://openalex.org/W1966557338","https://openalex.org/W2366931106"],"abstract_inverted_index":{"In":[0],"the":[1,13,32,43,81,85,91,98,103,112,123,129,140,148,152,165,172,175,185,191,196,199,203,207],"process":[2],"of":[3,35,66,83,115,142,174,198,206,210],"subway":[4,67,116,154],"construction,":[5],"there":[6],"is":[7,108,182],"a":[8,46,62,132],"complex":[9],"nonlinear":[10],"relationship":[11],"among":[12],"engineering":[14,93,120,149,155],"quantity,":[15],"material":[16],"cost,":[17,22,150],"labor":[18],"cost":[19,70,156,209],"and":[20,39,48,52,77,90,118,121,151,163,184,201],"total":[21],"which":[23],"cannot":[24],"be":[25],"accurately":[26],"calculated":[27],"by":[28],"manpower":[29],"alone.":[30],"Therefore,":[31],"reasonable":[33],"deployment":[34],"human,":[36],"material,":[37],"capital":[38],"other":[40],"resources":[41],"in":[42,97,179],"future":[44],"requires":[45],"high-precision":[47],"highly":[49],"reliable":[50],"analysis":[51,76,106],"prediction":[53,71,176,186],"model.":[54,166],"Aiming":[55],"at":[56],"this":[57,59,180],"problem,":[58],"paper":[60,181],"proposes":[61],"Bayesian":[63,133],"network":[64,134],"model":[65,135,177,200],"construction":[68,208],"project":[69],"based":[72],"on":[73,80,128],"principal":[74,104],"component":[75,105],"K2":[78,143],"algorithm":[79,144],"basis":[82],"analyzing":[84],"financial":[86],"data,":[87],"contract":[88],"data":[89,96,100,125,157],"existing":[92],"quantity":[94],"calculation":[95],"information":[99],"system.":[101],"Firstly,":[102],"method":[107],"used":[109,159],"to":[110,139,145,160],"screen":[111],"influencing":[113],"factors":[114],"mechanical":[117],"electrical":[119],"extract":[122],"core":[124],"features.":[126],"Based":[127],"extracted":[130],"features,":[131],"was":[136,158],"built":[137],"according":[138],"principle":[141],"dynamically":[146],"analyze":[147],"actual":[153],"train,":[161],"verify":[162],"predict":[164],"The":[167],"experimental":[168],"results":[169,187],"show":[170],"that":[171],"accuracy":[173],"proposed":[178],"87.5%,":[183],"are":[188],"completely":[189],"within":[190],"controllable":[192],"range,":[193],"thus":[194],"proving":[195],"effectiveness":[197],"realizing":[202],"dynamic":[204],"tracking":[205],"electromechanical":[211],"engineering.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
