{"id":"https://openalex.org/W3109470735","doi":"https://doi.org/10.1109/access.2020.3042329","title":"Expressway Project Cost Estimation With a Convolutional Neural Network Model","display_name":"Expressway Project Cost Estimation With a Convolutional Neural Network Model","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3109470735","doi":"https://doi.org/10.1109/access.2020.3042329","mag":"3109470735"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3042329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042329","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279313.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279313.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048892549","display_name":"Xiaojuan Xue","orcid":"https://orcid.org/0000-0003-3116-9151"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]},{"id":"https://openalex.org/I4210103140","display_name":"CCCC Highway Consultants (China)","ror":"https://ror.org/01bs84e19","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103140"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaojuan Xue","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","CCCC First Highway Consultants Company Ltd., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"CCCC First Highway Consultants Company Ltd., Xi'an, China","institution_ids":["https://openalex.org/I4210103140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101672410","display_name":"Yuanhua Jia","orcid":"https://orcid.org/0000-0002-1903-6041"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhua Jia","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035130214","display_name":"Yuanjie Tang","orcid":"https://orcid.org/0000-0002-3625-1333"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjie Tang","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3625-1333","affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4338,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.80299127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"217848","last_page":"217866"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9970999956130981,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9970999956130981,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9912999868392944,"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"}},{"id":"https://openalex.org/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9822999835014343,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.7811107635498047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7313922047615051},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6530367732048035},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6390018463134766},{"id":"https://openalex.org/keywords/cost-estimate","display_name":"Cost estimate","score":0.6108951568603516},{"id":"https://openalex.org/keywords/conceptual-design","display_name":"Conceptual design","score":0.4730733335018158},{"id":"https://openalex.org/keywords/stage","display_name":"Stage (stratigraphy)","score":0.43102535605430603},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4188169240951538},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4126025140285492},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3454206883907318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3303452730178833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2574349641799927},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15729302167892456},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.14627507328987122}],"concepts":[{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.7811107635498047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7313922047615051},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6530367732048035},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6390018463134766},{"id":"https://openalex.org/C93983250","wikidata":"https://www.wikidata.org/wiki/Q795053","display_name":"Cost estimate","level":2,"score":0.6108951568603516},{"id":"https://openalex.org/C120208923","wikidata":"https://www.wikidata.org/wiki/Q5158435","display_name":"Conceptual design","level":2,"score":0.4730733335018158},{"id":"https://openalex.org/C146357865","wikidata":"https://www.wikidata.org/wiki/Q1123245","display_name":"Stage (stratigraphy)","level":2,"score":0.43102535605430603},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4188169240951538},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4126025140285492},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3454206883907318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3303452730178833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2574349641799927},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15729302167892456},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.14627507328987122},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3042329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042329","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279313.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:da786687330e4f62a0393da37b1677a2","is_oa":true,"landing_page_url":"https://doaj.org/article/da786687330e4f62a0393da37b1677a2","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 217848-217866 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3042329","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042329","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09279313.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.49000000953674316}],"awards":[{"id":"https://openalex.org/G537356925","display_name":"\u4ea4\u901a\u8fd0\u8f93\u5efa\u8bbe\u5de5\u7a0b\u65bd\u5de5\u7ebf\u6027\u8ba1\u5212\u7f16\u5236\u65b9\u6cd5\u53ca\u4f18\u5316\u6a21\u578b\u4e0e\u7b97\u6cd5\u7814\u7a76","funder_award_id":"71801010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7665497758","display_name":null,"funder_award_id":"2020JBM033","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3109470735.pdf","grobid_xml":"https://content.openalex.org/works/W3109470735.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W597192057","https://openalex.org/W613938074","https://openalex.org/W628289812","https://openalex.org/W1582274366","https://openalex.org/W1969334115","https://openalex.org/W1979236264","https://openalex.org/W1985731029","https://openalex.org/W1987919596","https://openalex.org/W1996726633","https://openalex.org/W2001833513","https://openalex.org/W2012483090","https://openalex.org/W2016759211","https://openalex.org/W2030474209","https://openalex.org/W2036965124","https://openalex.org/W2037272884","https://openalex.org/W2064302126","https://openalex.org/W2071607705","https://openalex.org/W2079847520","https://openalex.org/W2087122156","https://openalex.org/W2100495367","https://openalex.org/W2112796928","https://openalex.org/W2124380327","https://openalex.org/W2128890213","https://openalex.org/W2149829835","https://openalex.org/W2150284203","https://openalex.org/W2156016826","https://openalex.org/W2181477644","https://openalex.org/W2519653196","https://openalex.org/W2562623872","https://openalex.org/W2606790217","https://openalex.org/W2621150303","https://openalex.org/W2742841115","https://openalex.org/W2776541877","https://openalex.org/W2802168276","https://openalex.org/W2884228899","https://openalex.org/W2894295805","https://openalex.org/W2906033034","https://openalex.org/W2919115771","https://openalex.org/W2919354935","https://openalex.org/W2921277556","https://openalex.org/W2945364798","https://openalex.org/W2947267692","https://openalex.org/W2950165444","https://openalex.org/W2956342231","https://openalex.org/W2967391408","https://openalex.org/W2979745608","https://openalex.org/W2999130725","https://openalex.org/W3086242700","https://openalex.org/W4285719527","https://openalex.org/W6618024191","https://openalex.org/W6678652958","https://openalex.org/W6685696430","https://openalex.org/W6730699326","https://openalex.org/W6763790396"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W1501776718","https://openalex.org/W657108774","https://openalex.org/W2615136228","https://openalex.org/W2390192952","https://openalex.org/W2373296418","https://openalex.org/W3213254966","https://openalex.org/W623587694","https://openalex.org/W2074187364","https://openalex.org/W136218537"],"abstract_inverted_index":{"With":[0],"the":[1,4,6,22,28,31,40,46,55,63,67,74,78,92,108,114,119,125,131,135,139,147,156,166,182,193],"development":[2],"of":[3,8,30,66,77,95,113,134,151,171,185],"economy,":[5],"prediction":[7,29,82,132,154,167],"expressway":[9,32,68,79,152,186],"project":[10,80,93,201],"costs":[11],"has":[12],"gained":[13],"increasing":[14],"research":[15,48,109],"attention.":[16],"In":[17,72,137],"this":[18,102,172],"study,":[19],"based":[20],"on":[21],"convolution":[23],"neural":[24],"network":[25],"(CNN)":[26],"algorithm,":[27],"construction":[33,187],"cost":[34,81,153,190],"was":[35],"analyzed":[36],"with":[37],"respect":[38],"to":[39,54,106,124,177,197],"conceptual":[41,69,194],"design":[42,70,195],"stage.":[43,71],"By":[44],"summarizing":[45],"existing":[47],"results,":[49],"10":[50,120],"new":[51,121],"factors":[52],"related":[53,123],"bridge":[56,126],"and":[57,85,127,159,162,188],"tunnel":[58,128],"are":[59],"creatively":[60],"introduced":[61],"into":[62],"cost-prediction":[64],"index":[65],"addition,":[73,138],"data":[75],"structure":[76],"is":[83,89,104,142],"defined":[84],"a":[86],"CNN":[87,140],"model":[88,141],"established.":[90],"Finally,":[91],"information":[94],"415":[96],"expressways":[97],"in":[98,101,181,203],"China":[99],"collected":[100],"study":[103,173],"used":[105,176],"verify":[107],"results.":[110],"The":[111,169],"results":[112],"case":[115],"analysis":[116],"show":[117],"that":[118],"indexes":[122],"can":[129,164,174],"improve":[130,165],"accuracy":[133],"model.":[136],"more":[143],"suitable":[144],"for":[145],"solving":[146],"high-dimensional":[148],"nonlinear":[149],"problem":[150],"than":[155],"conventional":[157],"artificial-neural-network":[158],"regression-analysis":[160],"models,":[161],"it":[163],"accuracy.":[168],"findings":[170],"be":[175],"devise":[178],"financial":[179],"plans":[180],"early":[183],"stage":[184,196],"facilitate":[189],"management":[191],"at":[192],"help":[198],"investors":[199],"acquire":[200],"funds":[202],"advance.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}