{"id":"https://openalex.org/W2062373098","doi":"https://doi.org/10.1109/cec.2007.4424587","title":"Parallel BMDA with probability model migration","display_name":"Parallel BMDA with probability model migration","publication_year":2007,"publication_date":"2007-09-01","ids":{"openalex":"https://openalex.org/W2062373098","doi":"https://doi.org/10.1109/cec.2007.4424587","mag":"2062373098"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2007.4424587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2007.4424587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Congress on Evolutionary Computation","raw_type":"proceedings-article"},"type":"conference-paper","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/A5059879181","display_name":"Ji\u0159\u00ed Jaro\u0161","orcid":"https://orcid.org/0000-0002-0087-8804"},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Jiri Jaros","raw_affiliation_strings":["The Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic","University of Technology Brno"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"University of Technology Brno","institution_ids":["https://openalex.org/I60587646"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112039278","display_name":"Josef Schwarz","orcid":null},"institutions":[{"id":"https://openalex.org/I60587646","display_name":"Brno University of Technology","ror":"https://ror.org/03613d656","country_code":"CZ","type":"education","lineage":["https://openalex.org/I60587646"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Josef Schwarz","raw_affiliation_strings":["The Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic","University of Technology Brno"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Faculty of Information Technology, Brno University of Technology, Brno, Czech Republic","institution_ids":["https://openalex.org/I60587646"]},{"raw_affiliation_string":"University of Technology Brno","institution_ids":["https://openalex.org/I60587646"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I60587646"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"1059","last_page":"1066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9860000014305115,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9860000014305115,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9812999963760376,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9253000020980835,"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/dependency","display_name":"Dependency (UML)","score":0.7888265252113342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6510177850723267},{"id":"https://openalex.org/keywords/bivariate-analysis","display_name":"Bivariate analysis","score":0.6398066282272339},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.5784074664115906},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.5479230880737305},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5251505374908447},{"id":"https://openalex.org/keywords/probability-model","display_name":"Probability model","score":0.47635793685913086},{"id":"https://openalex.org/keywords/marginal-distribution","display_name":"Marginal distribution","score":0.42681241035461426},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.42510196566581726},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41894668340682983},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40926551818847656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34488028287887573},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3367237150669098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2929450273513794},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2614139914512634},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.17952421307563782}],"concepts":[{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7888265252113342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510177850723267},{"id":"https://openalex.org/C64341305","wikidata":"https://www.wikidata.org/wiki/Q4919225","display_name":"Bivariate analysis","level":2,"score":0.6398066282272339},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.5784074664115906},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.5479230880737305},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5251505374908447},{"id":"https://openalex.org/C2984179964","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Probability model","level":2,"score":0.47635793685913086},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.42681241035461426},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.42510196566581726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41894668340682983},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40926551818847656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34488028287887573},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3367237150669098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2929450273513794},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2614139914512634},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.17952421307563782},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2007.4424587","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2007.4424587","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE Congress on Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2194280","https://openalex.org/W22752330","https://openalex.org/W103918058","https://openalex.org/W117154393","https://openalex.org/W191705817","https://openalex.org/W1479911746","https://openalex.org/W1497818865","https://openalex.org/W1509028783","https://openalex.org/W1517993545","https://openalex.org/W1537267443","https://openalex.org/W1538328348","https://openalex.org/W1541691514","https://openalex.org/W1547363087","https://openalex.org/W1564178912","https://openalex.org/W1574062351","https://openalex.org/W1587852158","https://openalex.org/W1600310449","https://openalex.org/W1604495723","https://openalex.org/W1786357191","https://openalex.org/W1971309542","https://openalex.org/W2114672569","https://openalex.org/W2133434503","https://openalex.org/W2139015486","https://openalex.org/W2170539222","https://openalex.org/W2414365832","https://openalex.org/W3154803405","https://openalex.org/W4230798657","https://openalex.org/W6607878208","https://openalex.org/W6628782388","https://openalex.org/W6632182870","https://openalex.org/W6634355359","https://openalex.org/W6635050186","https://openalex.org/W6636140920","https://openalex.org/W6676963755"],"related_works":["https://openalex.org/W4235062529","https://openalex.org/W2152457604","https://openalex.org/W1978117141","https://openalex.org/W2383655479","https://openalex.org/W2117322591","https://openalex.org/W2073622612","https://openalex.org/W2122857041","https://openalex.org/W2032285496","https://openalex.org/W4297670780","https://openalex.org/W2951801950"],"abstract_inverted_index":{"The":[0,25,41,76],"paper":[1],"presents":[2],"a":[3,33],"new":[4,45],"concept":[5,134],"of":[6,18,28,37,43,53,69,78,97,116,135],"parallel":[7],"bivariate":[8],"marginal":[9],"distribution":[10],"algorithm":[11],"using":[12,81],"the":[13,21,44,51,59,63,66,70,88,95,103,107,113,117,127,132],"stepping":[14],"stone":[15],"based":[16],"model":[17,39,56,73],"communication":[19],"with":[20,32],"unidirectional":[22],"ring":[23],"topology.":[24],"traditional":[26,133],"migration":[27],"individuals":[29],"is":[30,48,74,85,110],"compared":[31],"newly":[34],"proposed":[35,105,128],"technique":[36],"probability":[38,55,72],"migration.":[40,137],"idea":[42],"xBMDA":[46],"algorithms":[47],"to":[49,94],"modify":[50],"learning":[52,68],"classical":[54],"(applied":[57],"in":[58],"sequential":[60],"BMDA).":[61],"In":[62,102],"first":[64],"strategy,":[65,106],"adaptive":[67,129],"resident":[71,98,119],"used.":[75],"evaluation":[77,108],"pair":[79,91],"dependency,":[80],"Pearson's":[82],"chi-square":[83],"statistics":[84],"influenced":[86],"by":[87],"relevant":[89],"immigrant":[90,100,121],"dependency":[92],"according":[93],"quality":[96],"and":[99,120],"subpopulation.":[101,122],"second":[104],"metric":[109],"applied":[111],"for":[112],"diploid":[114],"mode":[115],"aggregated":[118],"Experimental":[123],"results":[124],"show":[125],"that":[126],"BMDA":[130],"outperforms":[131],"individual":[136]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}