{"id":"https://openalex.org/W2113816012","doi":"https://doi.org/10.1145/1068009.1068039","title":"Bayesian optimization models for particle swarms","display_name":"Bayesian optimization models for particle swarms","publication_year":2005,"publication_date":"2005-06-25","ids":{"openalex":"https://openalex.org/W2113816012","doi":"https://doi.org/10.1145/1068009.1068039","mag":"2113816012"},"language":"en","primary_location":{"id":"doi:10.1145/1068009.1068039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1068009.1068039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-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/A5110886409","display_name":"Christopher K. Monson","orcid":null},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Christopher K. Monson","raw_affiliation_strings":["Brigham Young University, Provo, UT"],"affiliations":[{"raw_affiliation_string":"Brigham Young University, Provo, UT","institution_ids":["https://openalex.org/I100005738"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029074659","display_name":"Kevin Seppi","orcid":"https://orcid.org/0000-0002-4932-2700"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin D. Seppi","raw_affiliation_strings":["Brigham Young University, Provo, UT"],"affiliations":[{"raw_affiliation_string":"Brigham Young University, Provo, UT","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110886409"],"corresponding_institution_ids":["https://openalex.org/I100005738"],"apc_list":null,"apc_paid":null,"fwci":3.5101,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.92923223,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"193","last_page":"200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9993000030517578,"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":0.9993000030517578,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9901000261306763,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7315950393676758},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6496174335479736},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.571790874004364},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.563200831413269},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5360211730003357},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4910860061645508},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.44895800948143005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4388185441493988},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34686338901519775},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32955583930015564},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12722516059875488}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7315950393676758},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6496174335479736},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.571790874004364},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.563200831413269},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5360211730003357},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4910860061645508},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.44895800948143005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4388185441493988},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34686338901519775},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32955583930015564},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12722516059875488},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1068009.1068039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1068009.1068039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th annual conference on Genetic and evolutionary computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W131206777","https://openalex.org/W1488420340","https://openalex.org/W1566471577","https://openalex.org/W1628481780","https://openalex.org/W1875348914","https://openalex.org/W1907706552","https://openalex.org/W1926832021","https://openalex.org/W1983362322","https://openalex.org/W2105934661","https://openalex.org/W2122410182","https://openalex.org/W2127931254","https://openalex.org/W2151554678","https://openalex.org/W2152195021","https://openalex.org/W2165299997","https://openalex.org/W2169245194","https://openalex.org/W2543580944","https://openalex.org/W2623293810","https://openalex.org/W6629385919","https://openalex.org/W6703967216"],"related_works":["https://openalex.org/W3106461837","https://openalex.org/W4283700523","https://openalex.org/W3168182983","https://openalex.org/W4387079005","https://openalex.org/W4321472004","https://openalex.org/W4221166418","https://openalex.org/W2968265130","https://openalex.org/W3199608561","https://openalex.org/W4401858220","https://openalex.org/W4382049207"],"abstract_inverted_index":{"We":[0],"explore":[1],"the":[2,11,22,39,81],"use":[3,23,32],"of":[4,13,24,33],"information":[5,36],"models":[6,26],"as":[7,38],"a":[8,28],"guide":[9],"for":[10,41,46,88],"development":[12],"single":[14],"objective":[15],"optimization":[16],"algorithms,":[17],"giving":[18],"particular":[19],"attention":[20],"to":[21,58,63],"Bayesian":[25],"in":[27],"PSO":[29,66],"context.":[30],"The":[31],"an":[34],"explicit":[35],"model":[37],"basis":[40],"particle":[42],"motion":[43],"provides":[44],"tools":[45,87],"designing":[47],"successful":[48],"algorithms.":[49],"One":[50],"such":[51],"algorithm":[52],"is":[53,68],"developed":[54,79],"and":[55,70,91],"shown":[56],"empirically":[57],"be":[59,78],"effective.":[60],"Its":[61],"relationship":[62],"other":[64],"popular":[65],"algorithms":[67,76],"explored":[69],"arguments":[71],"are":[72],"presented":[73],"that":[74],"those":[75],"may":[77],"from":[80],"same":[82],"model,":[83],"potentially":[84],"providing":[85],"new":[86],"their":[89],"analysis":[90],"tuning.":[92]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}