{"id":"https://openalex.org/W4413007325","doi":"https://doi.org/10.1142/s0129065725500583","title":"Evaluation of Bio-Inspired Models under Different Learning Settings for Energy Efficiency in Network Traffic Prediction","display_name":"Evaluation of Bio-Inspired Models under Different Learning Settings for Energy Efficiency in Network Traffic Prediction","publication_year":2025,"publication_date":"2025-08-06","ids":{"openalex":"https://openalex.org/W4413007325","doi":"https://doi.org/10.1142/s0129065725500583","pmid":"https://pubmed.ncbi.nlm.nih.gov/40843637"},"language":"en","primary_location":{"id":"doi:10.1142/s0129065725500583","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065725500583","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"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 Neural Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5099342282","display_name":"Theodoros Tsiolakis","orcid":null},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Theodoros Tsiolakis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021297224","display_name":"Nikolaos Pavlidis","orcid":"https://orcid.org/0000-0001-9370-5023"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikolaos Pavlidis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102721641","display_name":"Vasileios Perifanis","orcid":null},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Vasileios Perifanis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece","institution_ids":["https://openalex.org/I147962203"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047660023","display_name":"Pavlos S. Efraimidis","orcid":"https://orcid.org/0000-0003-3749-0165"},"institutions":[{"id":"https://openalex.org/I147962203","display_name":"Democritus University of Thrace","ror":"https://ror.org/03bfqnx40","country_code":"GR","type":"education","lineage":["https://openalex.org/I147962203"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Pavlos Efraimidis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Democritus University of Thrace, Xanthi 67100, Greece","institution_ids":["https://openalex.org/I147962203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5099342282"],"corresponding_institution_ids":["https://openalex.org/I147962203"],"apc_list":null,"apc_paid":null,"fwci":2.6124,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.91288319,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"35","issue":"12","first_page":"2550058","last_page":"2550058"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","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/T12611","display_name":"Neural Networks and Reservoir Computing","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.652109682559967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5384457111358643},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5326979160308838},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.46951955556869507},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.43151167035102844},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12806829810142517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11359983682632446},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08825936913490295}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.652109682559967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5384457111358643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5326979160308838},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.46951955556869507},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.43151167035102844},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12806829810142517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11359983682632446},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08825936913490295},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1142/s0129065725500583","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065725500583","pdf_url":null,"source":{"id":"https://openalex.org/S197665576","display_name":"International Journal of Neural Systems","issn_l":"0129-0657","issn":["0129-0657","1793-6462"],"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 Neural Systems","raw_type":"journal-article"},{"id":"pmid:40843637","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40843637","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International journal of neural systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2042013578","https://openalex.org/W2061005234","https://openalex.org/W2071269152","https://openalex.org/W2147101007","https://openalex.org/W2902524624","https://openalex.org/W2990138404","https://openalex.org/W3015205410","https://openalex.org/W3119054233","https://openalex.org/W3185149102","https://openalex.org/W3200350636","https://openalex.org/W3200813195","https://openalex.org/W3201870057","https://openalex.org/W3212169010","https://openalex.org/W4226178922","https://openalex.org/W4377428060","https://openalex.org/W4379017323","https://openalex.org/W4381165683","https://openalex.org/W4384302604","https://openalex.org/W4385322239","https://openalex.org/W4385484188","https://openalex.org/W4386623177","https://openalex.org/W4388483664","https://openalex.org/W4391308156","https://openalex.org/W4393305321","https://openalex.org/W4393906072","https://openalex.org/W4399891981","https://openalex.org/W4401705532","https://openalex.org/W4404102473"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Cellular":[0],"traffic":[1,98,240],"forecasting":[2],"is":[3,66],"a":[4,151],"critical":[5],"task":[6],"that":[7,180],"enables":[8],"network":[9],"operators":[10],"to":[11,34,121,149,198,206,215],"efficiently":[12],"allocate":[13],"resources":[14],"and":[15,36,53,88,108,118,125,145,171,186,237],"address":[16],"anomalies":[17],"in":[18,61,69,115,128,161,211,219],"rapidly":[19],"evolving":[20],"environments.":[21],"The":[22,100,177],"exponential":[23],"growth":[24],"of":[25,63,71,80,232],"data":[26,155],"collected":[27,156],"from":[28,157],"base":[29],"stations":[30],"poses":[31],"significant":[32,190],"challenges":[33],"processing":[35],"analysis.":[37],"While":[38],"machine":[39],"learning":[40],"(ML)":[41],"algorithms":[42],"have":[43],"emerged":[44],"as":[45,140,184],"powerful":[46],"tools":[47],"for":[48,96,235],"handling":[49],"these":[50,175],"large":[51],"datasets":[52],"providing":[54],"accurate":[55],"predictions,":[56],"their":[57,72,105,123,208],"environmental":[58],"impact,":[59],"particularly":[60,218],"terms":[62],"energy":[64,109,126,172,191,209],"consumption,":[65],"often":[67],"overlooked":[68],"favor":[70],"predictive":[73,106,169,195],"capabilities.":[74],"This":[75],"study":[76],"investigates":[77],"the":[78,166,230],"potential":[79,231],"two":[81],"bio-inspired":[82,134,181,222,233],"models:":[83],"Spiking":[84],"Neural":[85,142],"Networks":[86,94,143],"(SNNs)":[87],"Reservoir":[89],"Computing":[90],"through":[91],"Echo":[92],"State":[93],"(ESNs)":[95],"cellular":[97,239],"forecasting.":[99,241],"evaluation":[101],"focuses":[102],"on":[103],"both":[104,116],"performance":[107],"efficiency.":[110],"These":[111,224],"models":[112,135,234],"are":[113],"implemented":[114],"centralized":[117,216],"federated":[119,202],"settings":[120,213],"analyze":[122],"effectiveness":[124],"consumption":[127],"decentralized":[129,212],"systems.":[130],"Additionally,":[131],"we":[132,164],"compare":[133],"with":[136,221],"traditional":[137,199],"architectures,":[138],"such":[139,183],"Convolutional":[141],"(CNNs)":[144],"Multi-Layer":[146],"Perceptrons":[147],"(MLPs),":[148],"provide":[150],"comprehensive":[152],"evaluation.":[153],"Using":[154],"three":[158],"diverse":[159],"locations":[160],"Barcelona,":[162],"Spain,":[163],"examine":[165],"trade-offs":[167],"between":[168],"accuracy":[170,196],"demands":[173],"across":[174],"approaches.":[176],"results":[178],"indicate":[179],"models,":[182],"SNNs":[185],"ESNs,":[187],"can":[188],"achieve":[189],"savings":[192],"while":[193],"maintaining":[194],"comparable":[197],"architectures.":[200],"Furthermore,":[201],"implementations":[203],"were":[204],"tested":[205],"evaluate":[207],"efficiency":[210],"compared":[214],"systems,":[217],"combination":[220],"models.":[223],"findings":[225],"offer":[226],"valuable":[227],"insights":[228],"into":[229],"sustainable":[236],"privacy-preserving":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
