{"id":"https://openalex.org/W4411994548","doi":"https://doi.org/10.1007/s44163-025-00322-9","title":"Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting","display_name":"Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting","publication_year":2025,"publication_date":"2025-07-03","ids":{"openalex":"https://openalex.org/W4411994548","doi":"https://doi.org/10.1007/s44163-025-00322-9"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00322-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00322-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00322-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00322-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021811408","display_name":"Farideh Sobhanifard","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Farideh Sobhanifard","raw_affiliation_strings":["Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"Tehran, Iran","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5021811408"],"corresponding_institution_ids":[],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":5.2247,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95250832,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9986000061035156,"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":0.9986000061035156,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/fuzzy-logic","display_name":"Fuzzy logic","score":0.6746664047241211},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6084247827529907},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6013361215591431},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5649603009223938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5585290193557739},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5474954843521118},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5034484267234802},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.4886939823627472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4544421434402466}],"concepts":[{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6746664047241211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6084247827529907},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6013361215591431},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5649603009223938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5585290193557739},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5474954843521118},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5034484267234802},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4886939823627472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4544421434402466},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00322-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00322-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00322-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:81d79a74ae17492b914410ed6a02bd83","is_oa":true,"landing_page_url":"https://doaj.org/article/81d79a74ae17492b914410ed6a02bd83","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-11 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00322-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00322-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00322-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411994548.pdf","grobid_xml":"https://content.openalex.org/works/W4411994548.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1127095158","https://openalex.org/W1925428099","https://openalex.org/W1964810204","https://openalex.org/W1991797953","https://openalex.org/W1993596809","https://openalex.org/W2011873184","https://openalex.org/W2038817616","https://openalex.org/W2040355924","https://openalex.org/W2065385043","https://openalex.org/W2066141910","https://openalex.org/W2076063813","https://openalex.org/W2135646341","https://openalex.org/W2146726073","https://openalex.org/W2621177957","https://openalex.org/W2758694693","https://openalex.org/W2793529921","https://openalex.org/W2955169987","https://openalex.org/W2980795612","https://openalex.org/W3023725854","https://openalex.org/W3044960932","https://openalex.org/W3133636088","https://openalex.org/W3163645677","https://openalex.org/W3179455893","https://openalex.org/W3192802934","https://openalex.org/W4245926736","https://openalex.org/W4281728148","https://openalex.org/W4283080304","https://openalex.org/W4289920914","https://openalex.org/W4290981288","https://openalex.org/W4311210100","https://openalex.org/W4319072390","https://openalex.org/W4319339378","https://openalex.org/W4361002120","https://openalex.org/W4366426214","https://openalex.org/W4366981346","https://openalex.org/W4380742938","https://openalex.org/W4380768802","https://openalex.org/W4402675697"],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W3019402777","https://openalex.org/W2031835531","https://openalex.org/W2388590088","https://openalex.org/W4390822878","https://openalex.org/W4386596916","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Bayesian":[0,111,218],"network":[1,253],"is":[2,41,63,106,145,154,172,187],"a":[3,14,21,64,95],"form":[4],"of":[5,16,29,43,52,84,125,132,141,166,174,180,203,206,250],"graphical":[6],"model":[7,105],"for":[8,35,80,195],"identification":[9],"and":[10,70,102,116,128,189,197,209,224,233,239,243,254],"calculation":[11],"based":[12,161],"on":[13,49,162],"group":[15],"influential":[17],"variables,":[18],"related":[19],"to":[20,24,108,121,156,236,240,247],"probability":[22],"distribution":[23],"deal":[25],"with":[26,191],"the":[27,30,36,44,53,57,71,110,123,129,139,148,158,175,204,207,210,248,251,255],"complexity":[28],"model.":[31],"Providing":[32],"flexible":[33],"frameworks":[34],"Neural":[37,112,126,135,219],"Network":[38],"training":[39],"algorithm":[40,74,120],"one":[42,173],"topics":[45],"that":[46,75,216],"has":[47,76,88],"focused":[48],"many":[50],"issues":[51],"real":[54],"world.":[55],"On":[56],"other":[58],"hand,":[59],"Particle":[60,99],"Swarm":[61,100],"Optimization":[62,101],"computational":[65],"approach,":[66],"an":[67,181],"intelligent":[68],"optimization,":[69],"most":[72,176],"popular":[73],"been":[77],"widely":[78,177],"used":[79,155,178],"performing":[81],"such":[82],"types":[83,232],"optimization":[85],"problems,":[86],"which":[87,144,171],"faster":[89],"convergence.":[90],"Thus,":[91],"in":[92,114,134,201],"this":[93,152,185],"paper,":[94],"hybrid":[96,119],"innovative":[97],"Gaussian":[98],"fuzzy":[103],"logic":[104],"proposed":[107],"optimize":[109],"Networks":[113,127,136,220],"weight":[115],"structure.":[117],"A":[118],"improve":[122],"performance":[124,205],"total":[130],"number":[131],"weights":[133],"by":[137,147],"determining":[138],"size":[140],"each":[142],"particle,":[143],"inspired":[146],"prediction":[149],"process.":[150],"Furthermore,":[151],"method":[153],"forecast":[157],"economic":[159],"growth":[160],"time":[163,192],"series":[164,193],"dataset":[165],"Gross":[167],"Domestic":[168],"Product":[169],"(GDP),":[170],"measures":[179],"economy\u2019s":[182],"output.":[183],"Then,":[184],"approach":[186],"evaluated":[188],"compared":[190],"techniques":[194],"modeling":[196],"forecasting":[198],"selected":[199],"data":[200,231],"terms":[202],"standard":[208],"correlation":[211],"coefficient.":[212],"The":[213],"results":[214],"show":[215],"using":[217],"improves":[221],"structural":[222],"models":[223],"minimizes":[225],"operational":[226],"errors.":[227],"It":[228],"combines":[229],"different":[230],"prior":[234],"knowledge,":[235],"avoid":[237],"overfitting":[238],"handle":[241],"incomplete":[242],"noisy":[244],"data,":[245],"concerning":[246],"quality":[249],"learned":[252],"execution":[256],"time.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}