{"id":"https://openalex.org/W2493818576","doi":"https://doi.org/10.1142/s0219622016500395","title":"A New Breakpoint in Hybrid Particle Swarm-Neural Network Architecture: Individual Boundary Adjustment","display_name":"A New Breakpoint in Hybrid Particle Swarm-Neural Network Architecture: Individual Boundary Adjustment","publication_year":2016,"publication_date":"2016-08-03","ids":{"openalex":"https://openalex.org/W2493818576","doi":"https://doi.org/10.1142/s0219622016500395","mag":"2493818576"},"language":"en","primary_location":{"id":"doi:10.1142/s0219622016500395","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219622016500395","pdf_url":null,"source":{"id":"https://openalex.org/S207089700","display_name":"International Journal of Information Technology & Decision Making","issn_l":"0219-6220","issn":["0219-6220","1793-6845"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Technology &amp; Decision Making","raw_type":"journal-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/A5067307790","display_name":"Rahime Ceylan","orcid":"https://orcid.org/0000-0002-5814-1530"},"institutions":[{"id":"https://openalex.org/I137996928","display_name":"Sel\u00e7uk University","ror":"https://ror.org/045hgzm75","country_code":"TR","type":"education","lineage":["https://openalex.org/I137996928"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Rahime Ceylan","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Selcuk University 42250 Konya, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Selcuk University 42250 Konya, Turkey","institution_ids":["https://openalex.org/I137996928"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060301451","display_name":"Hasan Koyuncu","orcid":"https://orcid.org/0000-0003-4541-8833"},"institutions":[{"id":"https://openalex.org/I137996928","display_name":"Sel\u00e7uk University","ror":"https://ror.org/045hgzm75","country_code":"TR","type":"education","lineage":["https://openalex.org/I137996928"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Hasan Koyuncu","raw_affiliation_strings":["Department of Electrical and Electronics Engineering, Selcuk University 42250 Konya, Turkey"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronics Engineering, Selcuk University 42250 Konya, Turkey","institution_ids":["https://openalex.org/I137996928"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5067307790"],"corresponding_institution_ids":["https://openalex.org/I137996928"],"apc_list":null,"apc_paid":null,"fwci":2.25501503,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94761511,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"15","issue":"06","first_page":"1313","last_page":"1343"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9962000250816345,"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":0.9962000250816345,"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/T12676","display_name":"Machine Learning and ELM","score":0.9933000206947327,"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/T10320","display_name":"Neural Networks and Applications","score":0.9916999936103821,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.7040838003158569},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5296216607093811},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.5005443096160889},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4801723062992096},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4704305827617645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46215206384658813},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4274529814720154},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4029536545276642},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36163330078125},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10028204321861267}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.7040838003158569},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5296216607093811},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.5005443096160889},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4801723062992096},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4704305827617645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46215206384658813},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4274529814720154},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4029536545276642},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36163330078125},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10028204321861267}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0219622016500395","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0219622016500395","pdf_url":null,"source":{"id":"https://openalex.org/S207089700","display_name":"International Journal of Information Technology & Decision Making","issn_l":"0219-6220","issn":["0219-6220","1793-6845"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Technology &amp; Decision Making","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:wsi:ijitdm:v:15:y:2016:i:06:p:1313-1343","is_oa":false,"landing_page_url":"http://www.worldscientific.com/doi/abs/10.1142/S0219622016500395","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W154148467","https://openalex.org/W1132038451","https://openalex.org/W1529920312","https://openalex.org/W1820051232","https://openalex.org/W1833977909","https://openalex.org/W1875348914","https://openalex.org/W1964346230","https://openalex.org/W1967220039","https://openalex.org/W1967350113","https://openalex.org/W1971815679","https://openalex.org/W1975839640","https://openalex.org/W2003087683","https://openalex.org/W2010010720","https://openalex.org/W2021309800","https://openalex.org/W2024428474","https://openalex.org/W2035077248","https://openalex.org/W2046794274","https://openalex.org/W2063751653","https://openalex.org/W2064575768","https://openalex.org/W2076028496","https://openalex.org/W2076843176","https://openalex.org/W2077913352","https://openalex.org/W2079541639","https://openalex.org/W2091162263","https://openalex.org/W2097695383","https://openalex.org/W2110576630","https://openalex.org/W2116215023","https://openalex.org/W2140373607","https://openalex.org/W2143129497","https://openalex.org/W2152497556","https://openalex.org/W2166191038","https://openalex.org/W2167389327","https://openalex.org/W2186104583","https://openalex.org/W2303153816","https://openalex.org/W2327671165","https://openalex.org/W2543580944","https://openalex.org/W2728519294","https://openalex.org/W2971336636","https://openalex.org/W4236103016","https://openalex.org/W4399176852"],"related_works":["https://openalex.org/W3013085049","https://openalex.org/W1560496689","https://openalex.org/W4386900933","https://openalex.org/W4385301946","https://openalex.org/W4297797135","https://openalex.org/W3125672081","https://openalex.org/W1673581201","https://openalex.org/W2991991550","https://openalex.org/W2964287305","https://openalex.org/W3107918277"],"abstract_inverted_index":{"Neural":[0],"Network":[1],"(NN)":[2],"is":[3,47,125,144,218,327,332,347,351],"an":[4],"effective":[5],"classifier,":[6],"but":[7],"it":[8,183,326,350],"generally":[9],"uses":[10],"the":[11,39,81,90,113,122,134,181,322,339,343],"Backpropagation":[12],"type":[13],"algorithms":[14,34],"which":[15,79,198],"are":[16,35,71,106,118,209],"insufficient":[17],"because":[18],"of":[19,24,29,41,49,67,83,92,115,132,215,257,324,345],"trapping":[20],"to":[21,37,281],"local":[22],"minimum":[23],"error":[25],"rate.":[26],"For":[27],"elimination":[28],"this":[30,88],"handicap,":[31],"stochastic":[32],"optimization":[33],"used":[36],"update":[38],"parameters":[40],"NN.":[42,56],"Particle":[43],"Swarm":[44],"Optimization":[45],"(PSO)":[46],"one":[48],"these":[50],"providing":[51],"a":[52,190],"robust":[53],"coherence":[54],"with":[55,273],"In":[57,87,255,321],"realized":[58],"studies":[59],"about":[60,219,237],"Hybrid":[61],"PSO-NN,":[62],"position":[63,97,104],"and":[64,69,102,109,148,175,200,204,224,231,242,249,271,287,293,299,305,311,317,349],"velocity":[65,94,100],"boundaries":[66],"weight":[68,93,96],"bias":[70,99,103],"chosen":[72,367],"equal":[73],"or":[74,364],"set":[75,362],"free":[76,363],"in":[77,85,197,213],"space":[78],"leave":[80],"performance":[82,140],"PSO-NN":[84,129,188,260,263,272,331],"suspense.":[86],"paper,":[89],"limitations":[91,346],"(wv),":[95],"(wp),":[98],"(bv)":[101],"(bp)":[105],"diversely":[107],"changed":[108],"their":[110],"effects":[111],"on":[112,130,146,289,295,301,307,313,319],"output":[114],"hybrid":[116],"structure":[117,124],"examined.":[119],"Concerning":[120],"this,":[121],"formed":[123],"called":[126],"as":[127,284],"Bounded":[128,187,330],"account":[131],"adjusting":[133],"optimum":[135,340],"operating":[136],"conditions":[137,208],"(intervals).":[138],"On":[139],"evaluation,":[141],"proposed":[142],"method":[143],"tested":[145],"binary":[147],"multiclass":[149],"pattern":[150],"classification":[151,258],"by":[152],"using":[153],"six":[154],"medical":[155],"datasets:":[156],"Wisconsin":[157],"Breast":[158,172],"Cancer":[159],"(WBC),":[160],"Pima":[161],"Indian":[162],"Diabetes":[163],"(PID),":[164],"Bupa":[165],"Liver":[166],"Disorders":[167],"(BLD),":[168],"Heart":[169],"Statlog":[170],"(HS),":[171],"Tissue":[173],"(BT)":[174],"Dermatology":[176],"Data":[177],"(DD).":[178],"Upon":[179],"analyzing":[180],"results,":[182],"was":[184],"revealed":[185],"that":[186,329,353],"has":[189],"faster":[191],"processing":[192,216],"time":[193,217],"than":[194,334],"general":[195,335],"PSO-NNs":[196,336],"set-free":[199],"wpi[Formula:":[201],"see":[202,206,221,226,229,233,239,244,247,251,265,269],"text]bpi":[203,230,248,266],"wvi[Formula:":[205,232,250,268],"text]bvi":[207],"settled.":[210],"The":[211],"superiority":[212],"terms":[214,256],"199[Formula:":[220],"text]s":[222,227],"(set-free)":[223,241],"307[Formula:":[225],"(wpi[Formula:":[228,246,264],"text]bvi)":[234,252,270],"for":[235,253,337],"training,":[236],"16[Formula:":[238],"text]ms":[240,245],"9[Formula:":[243],"test.":[254],"performance,":[259],"(set-free":[261],"condition),":[262],"&amp;":[267],"individual":[274],"boundary":[275],"adjustment":[276],"(bounded":[277],"PSO-NN)":[278],"respectively":[279],"achieves":[280],"accuracy":[282],"rates":[283],"69.84%,":[285],"95.31%":[286],"97.22%":[288],"WBC,":[290],"47.01%,":[291],"76.69%":[292],"77.73%":[294],"PID,":[296],"55.36%,":[297],"67.54%":[298],"73.91%":[300],"BLD,":[302],"64.82%,":[303],"81.48%":[304],"85.56%":[306],"HS,":[308],"75%,":[309],"92.31%":[310,316],"100%":[312,318],"BT,":[314],"27.47%,":[315],"DD.":[320],"light":[323],"experiments,":[325],"seen":[328],"better":[333],"obtaining":[338],"results.":[341],"Consequently,":[342],"importance":[344],"clarified":[348],"proven":[352],"each":[354],"limitation":[355],"must":[356],"be":[357,361,366],"adjusted":[358],"individually,":[359],"not":[360,365],"equal.":[368]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
