{"id":"https://openalex.org/W7117786643","doi":"https://doi.org/10.3390/systems14010048","title":"Spatially Gated Mixture of Experts for Missing Data Imputation in Pavement Management Systems","display_name":"Spatially Gated Mixture of Experts for Missing Data Imputation in Pavement Management Systems","publication_year":2025,"publication_date":"2025-12-31","ids":{"openalex":"https://openalex.org/W7117786643","doi":"https://doi.org/10.3390/systems14010048"},"language":"en","primary_location":{"id":"doi:10.3390/systems14010048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010048","pdf_url":"https://www.mdpi.com/2079-8954/14/1/48/pdf?version=1767196223","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-8954/14/1/48/pdf?version=1767196223","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042251040","display_name":"Bongjun Ji","orcid":"https://orcid.org/0000-0002-2716-780X"},"institutions":[{"id":"https://openalex.org/I4921948","display_name":"Pusan National University","ror":"https://ror.org/01an57a31","country_code":"KR","type":"education","lineage":["https://openalex.org/I4921948"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bongjun Ji","raw_affiliation_strings":["Graduate School of Data Science, Pusan National University, Busan 46241, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Data Science, Pusan National University, Busan 46241, Republic of Korea","institution_ids":["https://openalex.org/I4921948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121663030","display_name":"Seungyeon Han","orcid":null},"institutions":[{"id":"https://openalex.org/I3019177047","display_name":"Korea Institute of Civil Engineering and Building Technology","ror":"https://ror.org/035enhp47","country_code":"KR","type":"government","lineage":["https://openalex.org/I2801339556","https://openalex.org/I3019177047","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungyeon Han","raw_affiliation_strings":["Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea","institution_ids":["https://openalex.org/I3019177047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056610166","display_name":"Mun-Sup Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I3019177047","display_name":"Korea Institute of Civil Engineering and Building Technology","ror":"https://ror.org/035enhp47","country_code":"KR","type":"government","lineage":["https://openalex.org/I2801339556","https://openalex.org/I3019177047","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Mun-Sup Lee","raw_affiliation_strings":["Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-2543-6981","affiliations":[{"raw_affiliation_string":"Korea Institute of Civil Engineering and Building Technology, Goyang-si 10223, Republic of Korea","institution_ids":["https://openalex.org/I3019177047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056610166"],"corresponding_institution_ids":["https://openalex.org/I3019177047"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59829465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"1","first_page":"48","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9488000273704529,"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":0.9488000273704529,"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/T10264","display_name":"Asphalt Pavement Performance Evaluation","score":0.011699999682605267,"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":0.00419999985024333,"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/missing-data","display_name":"Missing data","score":0.8982999920845032},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.8763999938964844},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5812000036239624},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.565500020980835},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.490200012922287},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.35429999232292175},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.3197999894618988}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8982999920845032},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.8763999938964844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6373999714851379},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6025000214576721},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5812000036239624},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.565500020980835},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.490200012922287},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.375900000333786},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.3197999894618988},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30300000309944153},{"id":"https://openalex.org/C2779714256","wikidata":"https://www.wikidata.org/wiki/Q25305062","display_name":"Multiple Models","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.26600000262260437},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/systems14010048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010048","pdf_url":"https://www.mdpi.com/2079-8954/14/1/48/pdf?version=1767196223","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:359bb2c43d974a53a1de6268852badba","is_oa":true,"landing_page_url":"https://doaj.org/article/359bb2c43d974a53a1de6268852badba","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":"Systems, Vol 14, Iss 1, p 48 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/systems14010048","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14010048","pdf_url":"https://www.mdpi.com/2079-8954/14/1/48/pdf?version=1767196223","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6268738508224487,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7117786643.pdf","grobid_xml":"https://content.openalex.org/works/W7117786643.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2025768430","https://openalex.org/W2064186732","https://openalex.org/W2096039506","https://openalex.org/W2496114304","https://openalex.org/W2901478763","https://openalex.org/W2955443275","https://openalex.org/W2964010366","https://openalex.org/W2965835972","https://openalex.org/W3008990987","https://openalex.org/W3035623224","https://openalex.org/W3170657538","https://openalex.org/W4206799843","https://openalex.org/W4280490195","https://openalex.org/W4306917520","https://openalex.org/W4367057034","https://openalex.org/W4380488416","https://openalex.org/W4385494244","https://openalex.org/W4391708430","https://openalex.org/W4392858613","https://openalex.org/W4400156346","https://openalex.org/W4400907450","https://openalex.org/W4401014315","https://openalex.org/W4401283468","https://openalex.org/W4401637078","https://openalex.org/W4403017038","https://openalex.org/W4403600294","https://openalex.org/W4408823290","https://openalex.org/W4411202387","https://openalex.org/W4413137600","https://openalex.org/W4414623799"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"imputation":[1,35,146],"of":[2,127],"missing":[3,83,88,92,97],"pavement-condition":[4],"data":[5,21],"is":[6,14,141,163],"critical":[7],"for":[8,144],"proactive":[9],"infrastructure":[10,145],"management,":[11],"yet":[12],"it":[13],"complicated":[15],"by":[16,42,182],"spatial":[17,40,122],"non-stationarity\u2014deterioration":[18],"patterns":[19],"and":[20,50,96,116,172],"quality":[22],"vary":[23],"markedly":[24],"across":[25],"regions.":[26],"This":[27],"study":[28],"proposes":[29],"a":[30,53,65,75],"Spatially":[31],"Gated":[32],"Mixture-of-Experts":[33],"(SG-MoE)":[34],"model":[36],"that":[37],"explicitly":[38],"encodes":[39],"heterogeneity":[41],"(i)":[43],"clustering":[44],"road":[45],"segments":[46],"using":[47],"geographic":[48],"coordinates":[49],"(ii)":[51],"supervising":[52],"gating":[54],"network":[55],"to":[56,60,165],"route":[57],"each":[58],"sample":[59],"region-specialized":[61],"expert":[62],"regressors.":[63],"Using":[64],"large-scale":[66],"national":[67],"pavement":[68],"management":[69],"database,":[70],"we":[71],"benchmark":[72],"SG-MoE":[73,102,162],"against":[74],"strong":[76],"baseline":[77,169],"under":[78,114,154,170,177],"controlled":[79],"missingness":[80,156],"mechanisms":[81],"(MCAR:":[82],"completely":[84],"at":[85,89,94,147,185],"random;":[86,90],"MAR:":[87],"MNAR:":[91],"not":[93],"random)":[95],"rates":[98],"(10\u201350%).":[99],"Across":[100,158],"scenarios,":[101],"consistently":[103],"matches":[104],"or":[105],"improves":[106,181],"upon":[107],"the":[108,110,117,166],"baseline;":[109],"largest":[111,175],"gains":[112,176],"occur":[113],"MCAR":[115],"challenging":[118],"MNAR":[119,178,187],"setting,":[120],"where":[121],"specialization":[123],"reduces":[124],"systematic":[125],"underestimation":[126],"high":[128],"crack-rate":[129],"sections.":[130],"The":[131],"results":[132,153],"provide":[133],"practical":[134],"guidance":[135],"on":[136],"when":[137],"spatially":[138],"aware":[139],"ensembling":[140],"most":[142],"beneficial":[143],"scale.":[148],"We":[149],"additionally":[150],"report":[151],"comparative":[152],"three":[155],"mechanisms.":[157],"five":[159],"random":[160],"seeds,":[161],"comparable":[164],"single":[167],"LightGBM":[168],"MCAR/MAR":[171],"achieves":[173],"its":[174],"(e.g.,":[179],"sMAPE":[180],"0.82":[183],"points":[184],"10%":[186],"missingness).":[188]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-12-31T00:00:00"}
