{"id":"https://openalex.org/W4385188507","doi":"https://doi.org/10.1145/3583133.3596390","title":"GECCO'2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework","display_name":"GECCO'2022 Symbolic Regression Competition: Post-Analysis of the Operon Framework","publication_year":2023,"publication_date":"2023-07-15","ids":{"openalex":"https://openalex.org/W4385188507","doi":"https://doi.org/10.1145/3583133.3596390"},"language":"en","primary_location":{"id":"doi:10.1145/3583133.3596390","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596390","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3583133.3596390","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071749418","display_name":"Bogdan Burlacu","orcid":"https://orcid.org/0000-0001-8785-2959"},"institutions":[{"id":"https://openalex.org/I4210136249","display_name":"University of Applied Sciences Upper Austria","ror":"https://ror.org/03jqp6d56","country_code":"AT","type":"education","lineage":["https://openalex.org/I4210136249"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Bogdan Burlacu","raw_affiliation_strings":["Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Hagenberg, Upper Austria, Austria"],"affiliations":[{"raw_affiliation_string":"Heuristic and Evolutionary Algorithms Laboratory, University of Applied Sciences Upper Austria, Hagenberg, Upper Austria, Austria","institution_ids":["https://openalex.org/I4210136249"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5071749418"],"corresponding_institution_ids":["https://openalex.org/I4210136249"],"apc_list":null,"apc_paid":null,"fwci":2.6224,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.91726604,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2412","last_page":"2419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998999834060669,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9998999834060669,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9896000027656555,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9800000190734863,"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/simplicity","display_name":"Simplicity","score":0.773543119430542},{"id":"https://openalex.org/keywords/symbolic-regression","display_name":"Symbolic regression","score":0.6878089904785156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6207033395767212},{"id":"https://openalex.org/keywords/competition","display_name":"Competition (biology)","score":0.4947366416454315},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48717138171195984},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.4811340868473053},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.47513821721076965},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47309353947639465},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.47061091661453247},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4595566987991333},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.4543078541755676},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4393789768218994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4351430833339691},{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.43256497383117676},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3524964451789856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2773984670639038},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.265395849943161},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21593177318572998},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08059114217758179},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.07686948776245117}],"concepts":[{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.773543119430542},{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.6878089904785156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6207033395767212},{"id":"https://openalex.org/C91306197","wikidata":"https://www.wikidata.org/wiki/Q45767","display_name":"Competition (biology)","level":2,"score":0.4947366416454315},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48717138171195984},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.4811340868473053},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.47513821721076965},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47309353947639465},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.47061091661453247},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4595566987991333},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.4543078541755676},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4393789768218994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4351430833339691},{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.43256497383117676},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3524964451789856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2773984670639038},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.265395849943161},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21593177318572998},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08059114217758179},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.07686948776245117},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"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/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3583133.3596390","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596390","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3583133.3596390","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3583133.3596390","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W173148493","https://openalex.org/W1973217014","https://openalex.org/W1984184112","https://openalex.org/W2008769248","https://openalex.org/W2054658115","https://openalex.org/W2168175751","https://openalex.org/W2236623899","https://openalex.org/W2417863416","https://openalex.org/W2593649365","https://openalex.org/W2599545620","https://openalex.org/W2915788561","https://openalex.org/W2949676527","https://openalex.org/W2991933648","https://openalex.org/W3040225824","https://openalex.org/W3046457509","https://openalex.org/W3209159738","https://openalex.org/W4220870416","https://openalex.org/W4281400719","https://openalex.org/W4281776274","https://openalex.org/W4289765664","https://openalex.org/W4393483259","https://openalex.org/W6893832806"],"related_works":["https://openalex.org/W2187402909","https://openalex.org/W4366821931","https://openalex.org/W4297435300","https://openalex.org/W1694810529","https://openalex.org/W2010638336","https://openalex.org/W2107985029","https://openalex.org/W2539131618","https://openalex.org/W113133661","https://openalex.org/W4385070502","https://openalex.org/W4386165561"],"abstract_inverted_index":{"Operon":[0,36],"is":[1],"a":[2,31,105],"C++":[3],"framework":[4],"for":[5,44,101],"symbolic":[6],"regression":[7,34],"with":[8,104],"the":[9,20,40,49,74,92,95,113,119,125,129,132,146],"ability":[10],"to":[11,27],"perform":[12],"local":[13],"search":[14],"by":[15,118,136],"optimizing":[16],"model":[17,137],"coefficients":[18],"using":[19],"Levenberg-Marquardt":[21],"algorithm.":[22,120],"This":[23],"enhancement":[24],"has":[25],"proven":[26],"be":[28],"effective":[29],"in":[30,39,83,139],"variety":[32],"of":[33,64,85,94,128],"tasks.":[35],"took":[37],"part":[38],"Interpretable":[41],"Symbolic":[42],"Regression":[43],"Data":[45],"Science":[46],"hosted":[47],"at":[48],"2022":[50],"Genetic":[51],"and":[52,80,110,150],"Evolutionary":[53],"Computation":[54],"Conference,":[55],"where":[56],"it":[57],"ranked":[58,81],"overall":[59,148],"4th":[60],"based":[61],"on":[62,124,154],"criteria":[63],"accuracy,":[65],"simplicity":[66],"as":[67,69],"well":[68],"task-specific":[70],"goals.":[71],"Although":[72],"accurate,":[73],"returned":[75,117],"models":[76,103],"were":[77],"exceedingly":[78],"complex":[79],"poorly":[82],"terms":[84],"simplicity.":[86],"In":[87],"this":[88],"paper,":[89],"we":[90],"investigate":[91],"application":[93],"Minimum":[96],"Description":[97],"Length":[98],"(MDL)":[99],"principle":[100],"selecting":[102],"better":[106],"compromise":[107],"between":[108],"accuracy":[109],"complexity":[111],"from":[112],"final":[114],"Pareto":[115],"front":[116],"A":[121],"new":[122],"experiment":[123],"synthetic":[126,156],"track":[127],"competition":[130],"highlights":[131],"critical":[133],"role":[134],"played":[135],"selection":[138],"algorithm":[140],"performance.":[141],"The":[142],"MDL-enhanced":[143],"approach":[144],"obtains":[145],"best":[147],"score":[149],"demonstrates":[151],"excellent":[152],"results":[153],"all":[155],"tracks.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
