{"id":"https://openalex.org/W3201169316","doi":"https://doi.org/10.1109/tits.2021.3106779","title":"A Deep Unsupervised Learning Approach for Airspace Complexity Evaluation","display_name":"A Deep Unsupervised Learning Approach for Airspace Complexity Evaluation","publication_year":2021,"publication_date":"2021-09-08","ids":{"openalex":"https://openalex.org/W3201169316","doi":"https://doi.org/10.1109/tits.2021.3106779","mag":"3201169316"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3106779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3106779","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-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/A5084998439","display_name":"Biyue Li","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Biyue Li","raw_affiliation_strings":["National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100629111","display_name":"Wenbo Du","orcid":"https://orcid.org/0000-0002-6561-6362"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Du","raw_affiliation_strings":["National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433693","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0003-1202-626X"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USA","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069910979","display_name":"Jun Chen","orcid":"https://orcid.org/0000-0002-0679-496X"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jun Chen","raw_affiliation_strings":["School of Engineering and Materials Science, Queen Mary University of London, London, U.K"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Materials Science, Queen Mary University of London, London, U.K","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021254405","display_name":"Ke Tang","orcid":"https://orcid.org/0000-0002-6236-2002"},"institutions":[{"id":"https://openalex.org/I3045169105","display_name":"Southern University of Science and Technology","ror":"https://ror.org/049tv2d57","country_code":"CN","type":"education","lineage":["https://openalex.org/I3045169105"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Tang","raw_affiliation_strings":["School of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China","institution_ids":["https://openalex.org/I3045169105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038809760","display_name":"Xianbin Cao","orcid":"https://orcid.org/0000-0002-5042-7884"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianbin Cao","raw_affiliation_strings":["National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Big Data Application Technologies for Comprehensive Traffic, School of Electronic and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5084998439"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":3.055,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.90751184,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"23","issue":"8","first_page":"11739","last_page":"11751"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9977999925613403,"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/T11489","display_name":"Air Traffic Management and Optimization","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6620590090751648},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.649554967880249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.57911217212677},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5461462736129761},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5234346389770508},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5050387978553772},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4998781681060791},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4599188566207886},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4585857093334198},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1893468201160431},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09006276726722717}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6620590090751648},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.649554967880249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.57911217212677},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5461462736129761},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5234346389770508},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5050387978553772},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4998781681060791},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4599188566207886},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4585857093334198},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1893468201160431},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09006276726722717},{"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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":2,"locations":[{"id":"doi:10.1109/tits.2021.3106779","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2021.3106779","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},{"id":"pmh:oai:qmro.qmul.ac.uk:123456789/74205","is_oa":false,"landing_page_url":"https://qmro.qmul.ac.uk/xmlui/handle/123456789/74205","pdf_url":null,"source":{"id":"https://openalex.org/S4306400530","display_name":"Queen Mary Research Online (Queen Mary University of London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I166337079","host_organization_name":"Queen Mary University of London","host_organization_lineage":["https://openalex.org/I166337079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G2575069074","display_name":null,"funder_award_id":"62088101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4048662016","display_name":null,"funder_award_id":"61961146005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4420704072","display_name":"TRANSIT: Towards a Robust Airport Decision Support System for Intelligent Taxiing","funder_award_id":"EP/N029496/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5219793275","display_name":null,"funder_award_id":"2019YFF0301400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5657975588","display_name":null,"funder_award_id":"EP/N029496/2","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1598228251","https://openalex.org/W1997441641","https://openalex.org/W2000834837","https://openalex.org/W2013092442","https://openalex.org/W2021232417","https://openalex.org/W2025768430","https://openalex.org/W2075578565","https://openalex.org/W2077264646","https://openalex.org/W2089468765","https://openalex.org/W2092432935","https://openalex.org/W2098310295","https://openalex.org/W2099299469","https://openalex.org/W2100495367","https://openalex.org/W2114354193","https://openalex.org/W2135905813","https://openalex.org/W2136111243","https://openalex.org/W2141198542","https://openalex.org/W2141860411","https://openalex.org/W2153157527","https://openalex.org/W2163922914","https://openalex.org/W2169535846","https://openalex.org/W2295598076","https://openalex.org/W2321866239","https://openalex.org/W2533069617","https://openalex.org/W2595619116","https://openalex.org/W2609216290","https://openalex.org/W2623326105","https://openalex.org/W2746398653","https://openalex.org/W2799012717","https://openalex.org/W2806018250","https://openalex.org/W2811487611","https://openalex.org/W2884105921","https://openalex.org/W2885006427","https://openalex.org/W2915337192","https://openalex.org/W2919115771","https://openalex.org/W2939176882","https://openalex.org/W2948156936","https://openalex.org/W2959490974","https://openalex.org/W2968157668","https://openalex.org/W2987793235","https://openalex.org/W2990257819","https://openalex.org/W2997574889","https://openalex.org/W3002481680","https://openalex.org/W3030488317","https://openalex.org/W3040359118","https://openalex.org/W3043476515","https://openalex.org/W3043515273","https://openalex.org/W3111817041","https://openalex.org/W4292692470","https://openalex.org/W6606297615","https://openalex.org/W6618697113","https://openalex.org/W6680375596","https://openalex.org/W6681096077","https://openalex.org/W6683161245","https://openalex.org/W6685380521","https://openalex.org/W6728550200","https://openalex.org/W6729448088","https://openalex.org/W6844244963","https://openalex.org/W6845122930"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W4375867731","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2075445622","https://openalex.org/W4220926404","https://openalex.org/W3123344745"],"abstract_inverted_index":{"Airspace":[0,20],"complexity":[1,21,126,152,212],"is":[2,173,179],"a":[3,30,51,69,119,130,140],"critical":[4],"metric":[5],"in":[6,29,58,84,192,208],"current":[7],"Air":[8],"Traffic":[9],"Management":[10],"systems":[11],"for":[12,108,124],"indicating":[13],"the":[14,81,86,90,94,109,147,166,186,205],"security":[15],"degree":[16],"of":[17,72,93,115,169,189,210],"airspace":[18,60,73,95,111,125,151,211],"operations.":[19],"can":[22],"be":[23,40,106],"affected":[24],"by":[25,77,135],"many":[26],"coupling":[27],"factors":[28],"complicated":[31],"and":[32,54,89,103,159],"nonlinear":[33],"way,":[34],"making":[35],"it":[36],"extremely":[37],"difficult":[38],"to":[39,80,144,150,163],"evaluated.":[41],"In":[42,113],"recent":[43],"years,":[44],"machine":[45,64],"learning":[46,65,122],"has":[47],"been":[48],"proved":[49],"as":[50],"promising":[52],"approach":[53,123,178],"achieved":[55],"significant":[56],"results":[57,197],"evaluating":[59],"complexity.":[61],"However,":[62],"existing":[63,170],"based":[66,128,184],"approaches":[67],"require":[68],"large":[70],"number":[71],"operational":[74,87],"data":[75,88,99,188],"labeled":[76],"experts.":[78],"Due":[79,162],"high":[82],"cost":[83],"labeling":[85],"dynamical":[91],"nature":[92],"operating":[96],"environment,":[97],"such":[98],"are":[100],"often":[101],"limited":[102],"may":[104],"not":[105],"suitable":[107],"changing":[110],"situation.":[112],"light":[114],"these,":[116],"we":[117],"propose":[118],"novel":[120],"unsupervised":[121,171,202],"evaluation":[127,213],"on":[129,185],"deep":[131,201],"neural":[132],"network":[133],"trained":[134],"unlabeled":[136],"samples.":[137],"We":[138],"introduce":[139],"new":[141],"loss":[142],"function":[143],"better":[145],"address":[146],"characteristics":[148],"pertaining":[149],"data,":[153],"including":[154],"dimension":[155],"coupling,":[156],"category":[157],"imbalance,":[158],"overlapped":[160],"boundaries.":[161],"these":[164],"characteristics,":[165],"generalization":[167],"ability":[168],"models":[172],"adversely":[174],"impacted.":[175],"The":[176],"proposed":[177],"validated":[180],"through":[181],"extensive":[182],"experiments":[183],"real-world":[187],"six":[190],"sectors":[191],"Southwestern":[193],"China":[194],"airspace.":[195],"Experimental":[196],"show":[198],"that":[199],"our":[200],"model":[203],"outperforms":[204],"state-of-the-art":[206],"methods":[207],"terms":[209],"accuracy.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}