{"id":"https://openalex.org/W3090510604","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206762","title":"Bio-inspired technique for improving machine learning speed and big data processing","display_name":"Bio-inspired technique for improving machine learning speed and big data processing","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3090510604","doi":"https://doi.org/10.1109/ijcnn48605.2020.9206762","mag":"3090510604"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9206762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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/A5039986288","display_name":"Andronicus A. Akinyelu","orcid":"https://orcid.org/0000-0003-2172-0755"},"institutions":[{"id":"https://openalex.org/I26999989","display_name":"University of the Free State","ror":"https://ror.org/009xwd568","country_code":"ZA","type":"education","lineage":["https://openalex.org/I26999989"]}],"countries":["ZA"],"is_corresponding":true,"raw_author_name":"Andronicus A Akinyelu","raw_affiliation_strings":["Department of Computer Science and Informatics, University of the Free State, Bloemfontein, South Africa"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Informatics, University of the Free State, Bloemfontein, South Africa","institution_ids":["https://openalex.org/I26999989"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5039986288"],"corresponding_institution_ids":["https://openalex.org/I26999989"],"apc_list":null,"apc_paid":null,"fwci":0.2651,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63580555,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9994999766349792,"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/T11891","display_name":"Big Data and Business Intelligence","score":0.9713000059127808,"subfield":{"id":"https://openalex.org/subfields/1404","display_name":"Management Information Systems"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9700999855995178,"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/big-data","display_name":"Big data","score":0.864045262336731},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.799005389213562},{"id":"https://openalex.org/keywords/ant-colony-optimization-algorithms","display_name":"Ant colony optimization algorithms","score":0.6589670181274414},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6152113080024719},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5992370843887329},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5950325727462769},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5776358842849731},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4699818193912506},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.46297046542167664},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4189970791339874},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4101560413837433}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.864045262336731},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.799005389213562},{"id":"https://openalex.org/C40128228","wikidata":"https://www.wikidata.org/wiki/Q460851","display_name":"Ant colony optimization algorithms","level":2,"score":0.6589670181274414},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6152113080024719},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5992370843887329},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5950325727462769},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5776358842849731},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4699818193912506},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.46297046542167664},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4189970791339874},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4101560413837433},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9206762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9206762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7400000095367432,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1965551184","https://openalex.org/W2011762057","https://openalex.org/W2041449151","https://openalex.org/W2126105956","https://openalex.org/W2158724449","https://openalex.org/W2487200295","https://openalex.org/W2741962935","https://openalex.org/W2889359136","https://openalex.org/W2905417435","https://openalex.org/W2921086987","https://openalex.org/W3120740533","https://openalex.org/W4211051123"],"related_works":["https://openalex.org/W2058965144","https://openalex.org/W2164382479","https://openalex.org/W2146343568","https://openalex.org/W98480971","https://openalex.org/W2150291671","https://openalex.org/W2013643406","https://openalex.org/W2027972911","https://openalex.org/W2157978810","https://openalex.org/W2597809628","https://openalex.org/W4389341988"],"abstract_inverted_index":{"Big":[0],"data":[1,47,67,148],"analytics":[2],"(BDA)":[3],"is":[4,75,85],"progressively":[5],"becoming":[6],"a":[7,53],"popular":[8],"practice":[9],"implemented":[10],"by":[11,77,114,136],"many":[12],"organizations,":[13],"because":[14],"of":[15,31,64,111,133,146],"its":[16],"potential":[17,105],"to":[18,106],"discover":[19],"treasured":[20],"insights":[21],"for":[22,36,60],"improved":[23],"decision-making.":[24],"Machine":[25],"Learning":[26],"(ML)":[27],"algorithms":[28,90,113],"are":[29],"one":[30],"the":[32,62,98,104,108,124,130,144],"effective":[33],"tools":[34],"used":[35],"BDA,":[37],"however,":[38],"their":[39,120],"computational":[40],"complexity":[41],"increases":[42],"with":[43],"an":[44],"increase":[45],"in":[46,80],"size.":[48],"Therefore,":[49],"this":[50],"paper":[51],"introduces":[52],"boundary":[54],"detection":[55],"and":[56,91,97],"instance":[57],"selection":[58,79],"technique":[59,72],"improving":[61,143],"speed":[63,110,145],"MLbased":[65],"big":[66,134,147],"classification":[68],"models.":[69],"The":[70],"proposed":[71],"(called":[73],"ACOISA_ML)":[74],"inspired":[76],"edge":[78],"ant":[81],"colony":[82],"optimization.":[83],"ACOISA_ML":[84],"evaluated":[86],"on":[87],"five":[88],"ML":[89,112],"ten":[92],"large-":[93],"or":[94],"medium-scale":[95],"datasets,":[96],"results":[99,125],"show":[100,126],"that":[101,127],"it":[102,128],"has":[103],"reduce":[107],"training":[109],"over":[115,137],"94%":[116],"without":[117],"significantly":[118],"affecting":[119],"prediction":[121],"accuracy.":[122],"Moreover,":[123],"reduced":[129],"storage":[131],"size":[132],"datasets":[135],"55%":[138],"(in":[139],"most":[140],"cases),":[141],"thus":[142],"processing.":[149]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
