{"id":"https://openalex.org/W4401009166","doi":"https://doi.org/10.1145/3675417.3675507","title":"Feature Selection Method Based on Improved Differential Evolution and ReliefF","display_name":"Feature Selection Method Based on Improved Differential Evolution and ReliefF","publication_year":2024,"publication_date":"2024-01-19","ids":{"openalex":"https://openalex.org/W4401009166","doi":"https://doi.org/10.1145/3675417.3675507"},"language":"en","primary_location":{"id":"doi:10.1145/3675417.3675507","doi":"https://doi.org/10.1145/3675417.3675507","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3675417.3675507","pdf_url":null,"source":{"id":"https://openalex.org/S7407087052","display_name":"Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5059071160","display_name":"Manting Yan","orcid":"https://orcid.org/0000-0001-7228-6253","observed_orcids":["https://orcid.org/0000-0001-7228-6253"]},"institutions":[{"id":"https://openalex.org/I4405281539","display_name":"Shenyang City University","ror":"https://ror.org/04gv5nz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Manting Yan","raw_affiliation_strings":["School of Intelligence and Engineering, Shenyang City University, China"],"raw_orcid":"https://orcid.org/0000-0001-7228-6253","affiliations":[{"raw_affiliation_string":"School of Intelligence and Engineering, Shenyang City University, China","institution_ids":["https://openalex.org/I4405281539"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jinyu Deng","orcid":"https://orcid.org/0009-0000-7316-3183","observed_orcids":["https://orcid.org/0009-0000-7316-3183"]},"institutions":[{"id":"https://openalex.org/I4405281539","display_name":"Shenyang City University","ror":"https://ror.org/04gv5nz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyu Deng","raw_affiliation_strings":["School of Intelligence and Engineering, Shenyang City University, China"],"raw_orcid":"https://orcid.org/0009-0000-7316-3183","affiliations":[{"raw_affiliation_string":"School of Intelligence and Engineering, Shenyang City University, China","institution_ids":["https://openalex.org/I4405281539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105097821","display_name":"Shuye Zhang","orcid":"https://orcid.org/0009-0002-4277-8462","observed_orcids":["https://orcid.org/0009-0002-4277-8462"]},"institutions":[{"id":"https://openalex.org/I4405281539","display_name":"Shenyang City University","ror":"https://ror.org/04gv5nz22","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405281539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuye Zhang","raw_affiliation_strings":["School of Intelligence and Engineering, Shenyang City University, China"],"raw_orcid":"https://orcid.org/0009-0002-4277-8462","affiliations":[{"raw_affiliation_string":"School of Intelligence and Engineering, Shenyang City University, China","institution_ids":["https://openalex.org/I4405281539"]}]},{"author_position":"last","author":{"id":null,"display_name":"Pengyu Chen","orcid":"https://orcid.org/0009-0009-1925-9219","observed_orcids":["https://orcid.org/0009-0009-1925-9219"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pengyu Chen","raw_affiliation_strings":["BMW Brilliance Automotive Ltd. Lydia Plant body shop Framing Area, China"],"raw_orcid":"https://orcid.org/0009-0009-1925-9219","affiliations":[{"raw_affiliation_string":"BMW Brilliance Automotive Ltd. Lydia Plant body shop Framing Area, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3054,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50447172,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"539","last_page":"543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.4961000084877014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.4961000084877014,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.3142000138759613,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10057","display_name":"Face and Expression Recognition","score":0.05260000005364418,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/feature-selection","display_name":"feature selection","score":0.9750000238418579},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"differential evolution","score":0.6639999747276306},{"id":"https://openalex.org/keywords/relieff","display_name":"ReliefF","score":0.968999981880188},{"id":"https://openalex.org/keywords/high-dimensional-data","display_name":"high-dimensional data","score":0.765999972820282},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"feature extraction","score":0.9430000185966492},{"id":"https://openalex.org/keywords/classification","display_name":"classification","score":0.38600000739097595},{"id":"https://openalex.org/keywords/population-diversity","display_name":"population diversity","score":0.35600000619888306}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699931859970093},{"id":"https://openalex.org/C74750220","wikidata":"https://www.wikidata.org/wiki/Q2662197","display_name":"Differential evolution","level":2,"score":0.7642782926559448},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7202633619308472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6277526617050171},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5723056793212891},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5629624724388123},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5249069929122925},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3972328305244446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3932284712791443},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3675417.3675507","doi":"https://doi.org/10.1145/3675417.3675507","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3675417.3675507","pdf_url":null,"source":{"id":"https://openalex.org/S7407087052","display_name":"Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1444952417","https://openalex.org/W1595159159","https://openalex.org/W2084812512","https://openalex.org/W2612473079","https://openalex.org/W2989585968"],"related_works":["https://openalex.org/W2587295215","https://openalex.org/W40679089","https://openalex.org/W4412109297","https://openalex.org/W3133614530","https://openalex.org/W582829353","https://openalex.org/W4396883664","https://openalex.org/W7134950424","https://openalex.org/W4417085065","https://openalex.org/W4400218175","https://openalex.org/W4387005569"],"abstract_inverted_index":{"In":[0],"addressing":[1],"the":[2,29,34,50,57,72,76,82,91,94],"challenge":[3],"of":[4,24,65,75,84,93],"difficult":[5],"coupled":[6],"feature":[7,17,54,66,86,98],"selection":[8,18,68],"in":[9,97],"high-dimensional":[10],"sample":[11],"environments,":[12],"this":[13],"paper":[14],"proposes":[15],"a":[16,22],"method":[19],"based":[20],"on":[21,46],"combination":[23],"improved":[25,58,73],"differential":[26,59,77],"evolution":[27,60,78],"and":[28],"ReliefF":[30,35],"algorithm":[31,36,96],"(MRDE).":[32],"Initially,":[33],"is":[37,69],"employed":[38],"to":[39],"filter":[40],"out":[41],"features":[42,52,102],"with":[43,100],"weaker":[44],"impacts":[45],"classification":[47,105],"results.":[48],"Subsequently,":[49],"remaining":[51],"undergo":[53],"extraction":[55],"using":[56],"algorithm.":[61],"The":[62],"enhanced":[63],"diversity":[64],"set":[67],"achieved":[70],"through":[71],"cross-strategy":[74],"algorithm,":[79],"thereby":[80],"resolving":[81],"issue":[83],"multi-coupled":[85],"selection.":[87],"Experimental":[88],"results":[89],"demonstrate":[90],"effectiveness":[92],"proposed":[95],"extraction,":[99],"extracted":[101],"exhibiting":[103],"strong":[104],"accuracy.":[106]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2024-07-27T00:00:00"}