{"id":"https://openalex.org/W4386609326","doi":"https://doi.org/10.1109/tgrs.2023.3314079","title":"A Multistrategy Evolutionary Multiobjective Optimization Method for Hyperspectral Endmember Extraction","display_name":"A Multistrategy Evolutionary Multiobjective Optimization Method for Hyperspectral Endmember Extraction","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386609326","doi":"https://doi.org/10.1109/tgrs.2023.3314079"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3314079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3314079","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5001257337","display_name":"Chuanlong Ye","orcid":"https://orcid.org/0000-0002-4145-0855"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chuanlong Ye","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100660581","display_name":"Fazhi He","orcid":"https://orcid.org/0000-0001-7016-3698"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fazhi He","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7016-3698","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036134594","display_name":"Jinkun Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinkun Luo","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010446011","display_name":"Lyuyang Tong","orcid":"https://orcid.org/0000-0001-7148-3618"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lyuyang Tong","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7148-3618","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102010696","display_name":"Xiaoxin Gao","orcid":"https://orcid.org/0000-0001-9514-9083"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxin Gao","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9514-9083","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057635087","display_name":"Tongzhen Si","orcid":"https://orcid.org/0000-0002-1141-9718"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongzhen Si","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-1141-9718","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084161986","display_name":"Linkun Fan","orcid":"https://orcid.org/0000-0002-9609-7497"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linkun Fan","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5001257337"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.7791,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75671354,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9746000170707703,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/endmember","display_name":"Endmember","score":0.9602956771850586},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7541980743408203},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6220253705978394},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5785314440727234},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5406084060668945},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.5234567523002625},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5179539918899536},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4696561396121979},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4674540162086487},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4254434406757355},{"id":"https://openalex.org/keywords/sort","display_name":"sort","score":0.41368138790130615},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3831944465637207},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3355215787887573},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32285988330841064},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.28161299228668213}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9602956771850586},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7541980743408203},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6220253705978394},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5785314440727234},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5406084060668945},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.5234567523002625},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5179539918899536},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4696561396121979},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4674540162086487},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4254434406757355},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.41368138790130615},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3831944465637207},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3355215787887573},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32285988330841064},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28161299228668213},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3314079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3314079","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6938322489","display_name":null,"funder_award_id":"62072348","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W1582058549","https://openalex.org/W1865089935","https://openalex.org/W1966536048","https://openalex.org/W2009576740","https://openalex.org/W2013885787","https://openalex.org/W2030295525","https://openalex.org/W2042564283","https://openalex.org/W2058484777","https://openalex.org/W2091383099","https://openalex.org/W2106334424","https://openalex.org/W2116699851","https://openalex.org/W2125298866","https://openalex.org/W2126105956","https://openalex.org/W2140216497","https://openalex.org/W2142786738","https://openalex.org/W2144492104","https://openalex.org/W2152195021","https://openalex.org/W2153885347","https://openalex.org/W2163886442","https://openalex.org/W2191172738","https://openalex.org/W2232388203","https://openalex.org/W2247116885","https://openalex.org/W2589747247","https://openalex.org/W2590646629","https://openalex.org/W2620694408","https://openalex.org/W2788240893","https://openalex.org/W2808993793","https://openalex.org/W2890623757","https://openalex.org/W2911903621","https://openalex.org/W2927240970","https://openalex.org/W2950964158","https://openalex.org/W2967530387","https://openalex.org/W3039625014","https://openalex.org/W3083662577","https://openalex.org/W3126601808","https://openalex.org/W3130652158","https://openalex.org/W3133876759","https://openalex.org/W3139578059","https://openalex.org/W3154568172","https://openalex.org/W3200952508","https://openalex.org/W3206855797","https://openalex.org/W4220801425","https://openalex.org/W4237234927","https://openalex.org/W4281395053","https://openalex.org/W4281568429","https://openalex.org/W4282913008","https://openalex.org/W4285223668","https://openalex.org/W4296934624","https://openalex.org/W4297310200","https://openalex.org/W4298325907","https://openalex.org/W4319069094","https://openalex.org/W4319836815","https://openalex.org/W4319866035","https://openalex.org/W4364380790","https://openalex.org/W4366310774","https://openalex.org/W4379230331","https://openalex.org/W4383220030","https://openalex.org/W6639379129"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W2890371384","https://openalex.org/W2315521504","https://openalex.org/W2006559622","https://openalex.org/W2040756827","https://openalex.org/W2051769241","https://openalex.org/W2773863718"],"abstract_inverted_index":{"Hyperspectral":[0],"endmember":[1,82,164,245],"extraction":[2,246],"(HEE)":[3],"is":[4,44,120,192,205,222,241],"an":[5,100,163,217],"essential":[6],"part":[7],"of":[8,37,116,161,178],"remote-sensing":[9],"image":[10],"processing.":[11],"There":[12],"have":[13,157],"been":[14],"recent":[15],"attempts":[16],"to":[17,31,50,91,108,122,153,156,224,243],"model":[18],"the":[19,33,38,47,77,98,112,117,149,186,195,202,212,238],"HEE":[20,40],"as":[21],"a":[22,66,105,158,175],"multiobjective":[23,28,69],"optimization":[24],"problem":[25],"and":[26,54,76,94,127],"apply":[27],"evolutionary":[29,68],"algorithms":[30,49,89],"solve":[32],"problem.":[34],"However,":[35],"because":[36],"large":[39],"search":[41,209],"space,":[42],"it":[43],"difficult":[45],"for":[46,81,138,198,207],"current":[48],"achieve":[51],"exploration\u2013exploitation":[52],"balance,":[53],"they":[55],"easily":[56],"stall":[57],"prematurely.":[58],"To":[59],"address":[60],"these":[61],"issues,":[62],"this":[63],"article":[64],"proposes":[65],"multistrategy":[67],"method":[70,85,107,240],"based":[71,140,210],"on":[72,111,141,194,211],"roulette":[73,189],"wheel":[74,190],"selection":[75,191],"genetic":[78,213],"algorithm":[79,214],"(RWS-GA)":[80],"extraction.":[83],"This":[84],"designs":[86],"two":[87],"parallel":[88],"corresponding":[90],"global":[92,199],"exploration":[93],"local":[95,208],"exploitation.":[96],"In":[97,169],"RWS-GA,":[99],"improved":[101],"NSGA-II":[102],"method,":[103],"adopting":[104],"novel":[106],"sort":[109],"individuals":[110,124,172,227],"same":[113],"front":[114],"instead":[115],"crowding":[118],"distance,":[119],"proposed":[121,239],"divide":[123],"into":[125],"superior":[126,203,242],"inferior":[128,183,196],"subpopulations.":[129],"Thereafter,":[130],"different":[131],"modified":[132],"population":[133,150],"update":[134],"strategies":[135],"are":[136,151],"utilized":[137],"subpopulations":[139],"characteristics.":[142],"Pixels":[143],"that":[144,237],"appear":[145],"more":[146],"frequently":[147],"in":[148,230,248],"considered":[152],"perform":[154],"better":[155],"higher":[159,176],"probability":[160,177],"forming":[162],"set":[165],"with":[166,182],"other":[167,244],"pixels.":[168],"addition,":[170],"excellent":[171],"often":[173],"exhibit":[174],"including":[179],"endmembers":[180],"compared":[181],"individuals.":[184],"Considering":[185],"abovementioned":[187],"opinions,":[188],"performed":[193],"subpopulation":[197,204],"search.":[200],"Meanwhile,":[201],"responsible":[206],"(GA).":[215],"Furthermore,":[216],"offspring":[218],"complement":[219],"mechanism":[220],"(OCM)":[221],"presented":[223],"prevent":[225],"duplicate":[226],"from":[228],"appearing":[229],"historical":[231],"archives.":[232],"Numerous":[233],"comparative":[234],"experiments":[235],"show":[236],"methods":[247],"three":[249],"real-world":[250],"datasets.":[251]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}