{"id":"https://openalex.org/W2079682462","doi":"https://doi.org/10.1109/ijcnn.2014.6889954","title":"Clustering of the self-organizing map using particle swarm optimization and validity indices","display_name":"Clustering of the self-organizing map using particle swarm optimization and validity indices","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2079682462","doi":"https://doi.org/10.1109/ijcnn.2014.6889954","mag":"2079682462"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","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/A5012478671","display_name":"Leonardo Enzo Brito da Silva","orcid":"https://orcid.org/0000-0003-3639-9175"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Leonardo Enzo Brito da Silva","raw_affiliation_strings":["Department of Electrical Engineering, Federal University of Rio Grande do Norte, Natal-RN, Brazil","Dept. of Electr. Eng., Fed. Univ. of Rio Grande do Norte, Rio Grande, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Federal University of Rio Grande do Norte, Natal-RN, Brazil","institution_ids":["https://openalex.org/I35046152"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Fed. Univ. of Rio Grande do Norte, Rio Grande, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025179228","display_name":"Jos\u00e9 Alfredo Ferreira Costa","orcid":"https://orcid.org/0000-0002-1290-6454"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jose Alfredo Ferreira Costa","raw_affiliation_strings":["Department of Electrical Engineering, Federal University of Rio Grande do Norte, Natal-RN, Brazil","Dept. of Electr. Eng., Fed. Univ. of Rio Grande do Norte, Rio Grande, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Federal University of Rio Grande do Norte, Natal-RN, Brazil","institution_ids":["https://openalex.org/I35046152"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Fed. Univ. of Rio Grande do Norte, Rio Grande, Brazil","institution_ids":["https://openalex.org/I35046152"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I35046152"],"apc_list":null,"apc_paid":null,"fwci":0.2068,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.48115557,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"30","issue":null,"first_page":"3798","last_page":"3806"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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/T10320","display_name":"Neural Networks and Applications","score":0.9991000294685364,"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":0.996399998664856,"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"}},{"id":"https://openalex.org/T13717","display_name":"Advanced Algorithms and Applications","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.818433403968811},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7705011963844299},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.5934413075447083},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5607673525810242},{"id":"https://openalex.org/keywords/fitness-function","display_name":"Fitness function","score":0.557730495929718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4789074659347534},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4743320345878601},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.47047004103660583},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4439801275730133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40582120418548584},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36278289556503296},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3507941961288452},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3222966194152832},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3146264851093292},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.08590191602706909}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.818433403968811},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7705011963844299},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5934413075447083},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5607673525810242},{"id":"https://openalex.org/C176066374","wikidata":"https://www.wikidata.org/wiki/Q629118","display_name":"Fitness function","level":3,"score":0.557730495929718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4789074659347534},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4743320345878601},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.47047004103660583},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4439801275730133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40582120418548584},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36278289556503296},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3507941961288452},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3222966194152832},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3146264851093292},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.08590191602706909},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889954","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889954","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4699999988079071,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W17277982","https://openalex.org/W17418856","https://openalex.org/W65738273","https://openalex.org/W183111108","https://openalex.org/W1505353324","https://openalex.org/W1518498072","https://openalex.org/W1536929369","https://openalex.org/W1595159159","https://openalex.org/W1874332895","https://openalex.org/W1879678483","https://openalex.org/W1981566656","https://openalex.org/W1981948263","https://openalex.org/W1992419399","https://openalex.org/W2011430131","https://openalex.org/W2011599294","https://openalex.org/W2016381774","https://openalex.org/W2025649768","https://openalex.org/W2048365415","https://openalex.org/W2060979493","https://openalex.org/W2066226535","https://openalex.org/W2079810998","https://openalex.org/W2088709281","https://openalex.org/W2101938621","https://openalex.org/W2107317146","https://openalex.org/W2110802877","https://openalex.org/W2111004121","https://openalex.org/W2118382442","https://openalex.org/W2124776405","https://openalex.org/W2142363274","https://openalex.org/W2145113795","https://openalex.org/W2165841251","https://openalex.org/W2169838897","https://openalex.org/W2319660501","https://openalex.org/W2482589566","https://openalex.org/W2538115256","https://openalex.org/W3023708208","https://openalex.org/W3036846224","https://openalex.org/W3120740533","https://openalex.org/W4206209869","https://openalex.org/W4235169531","https://openalex.org/W4244494905","https://openalex.org/W4245176872","https://openalex.org/W4248055113","https://openalex.org/W4248819226","https://openalex.org/W6600691717","https://openalex.org/W6600709823","https://openalex.org/W6630985644","https://openalex.org/W6676671362","https://openalex.org/W6779887223"],"related_works":["https://openalex.org/W2034551444","https://openalex.org/W2023416609","https://openalex.org/W2051216975","https://openalex.org/W2982550593","https://openalex.org/W1844640764","https://openalex.org/W2144077772","https://openalex.org/W2978573861","https://openalex.org/W3134384462","https://openalex.org/W2125094050","https://openalex.org/W2540137049"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3],"automatic":[4],"clustering":[5],"algorithm":[6],"applied":[7,120],"to":[8,24,91,112,121],"self-organizing":[9],"map":[10],"(SOM)":[11],"neurons":[12],"is":[13,62],"presented.":[14],"The":[15,39],"connections":[16],"of":[17,28,31,33,41,73,77,84,116],"the":[18,42,54,59,63,85,114,117],"SOM":[19],"grid":[20],"are":[21,45,109],"pruned":[22],"according":[23],"a":[25,29,96],"weighted":[26,43],"sum":[27,44],"set":[30],"measures":[32],"connection":[34],"strength":[35],"between":[36,66,99],"adjacent":[37],"neurons.":[38],"coefficients":[40],"obtained":[46],"through":[47,81],"particle":[48],"swarm":[49],"optimization":[50],"(PSO)":[51],"search":[52],"in":[53],"multidimensional":[55],"problem":[56],"space,":[57],"where":[58],"fitness":[60],"function":[61],"composed":[64],"density":[65],"and":[67,102,123],"within":[68],"clusters":[69],"(CDbw)":[70],"validity":[71],"index":[72],"strongly":[74],"connected":[75],"groups":[76],"neurons,":[78],"while":[79],"scanning":[80],"different":[82],"values":[83],"minimum":[86],"cluster":[87],"size":[88],"so":[89],"as":[90],"find":[92],"stable":[93],"regions":[94],"with":[95],"reasonable":[97],"trade-off":[98],"their":[100,103],"length":[101],"mean":[104],"CDbw":[105],"value.":[106],"Simulation":[107],"results":[108],"further":[110],"presented":[111],"show":[113],"performance":[115],"proposed":[118],"method":[119],"synthetic":[122],"real":[124],"world":[125],"datasets.":[126]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}