{"id":"https://openalex.org/W4318002289","doi":"https://doi.org/10.1109/is57118.2022.10019673","title":"Why Use Evolving Neuro-Fuzzy and Spiking Neural Networks for incremental and explainable learning of time series? A case study on predictive modelling of trade imports and outlier detection","display_name":"Why Use Evolving Neuro-Fuzzy and Spiking Neural Networks for incremental and explainable learning of time series? A case study on predictive modelling of trade imports and outlier detection","publication_year":2022,"publication_date":"2022-10-12","ids":{"openalex":"https://openalex.org/W4318002289","doi":"https://doi.org/10.1109/is57118.2022.10019673"},"language":"en","primary_location":{"id":"doi:10.1109/is57118.2022.10019673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is57118.2022.10019673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th International Conference on Intelligent Systems (IS)","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/A5080877283","display_name":"Iman AbouHassan","orcid":"https://orcid.org/0000-0001-5552-1311"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Iman Abouhassan","raw_affiliation_strings":["Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]},{"raw_affiliation_string":"Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024893012","display_name":"Nikola Kasabov","orcid":"https://orcid.org/0000-0003-4433-7521"},"institutions":[{"id":"https://openalex.org/I138801177","display_name":"University of Ulster","ror":"https://ror.org/01yp9g959","country_code":"GB","type":"education","lineage":["https://openalex.org/I138801177"]},{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["GB","NZ"],"is_corresponding":false,"raw_author_name":"Nikola Kasabov","raw_affiliation_strings":["Auckland University of Technology,KEDRI- SECMS,Auckland,New Zealand","Ulster Universty, UK","KEDRI- SECMS, Auckland University of Technology, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Auckland University of Technology,KEDRI- SECMS,Auckland,New Zealand","institution_ids":["https://openalex.org/I39854758"]},{"raw_affiliation_string":"Ulster Universty, UK","institution_ids":["https://openalex.org/I138801177"]},{"raw_affiliation_string":"KEDRI- SECMS, Auckland University of Technology, Auckland, New Zealand","institution_ids":["https://openalex.org/I39854758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055848730","display_name":"George Popov","orcid":"https://orcid.org/0000-0002-2150-9127"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"George Popov","raw_affiliation_strings":["Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]},{"raw_affiliation_string":"Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104198887","display_name":"Roumen Trifonov","orcid":"https://orcid.org/0000-0001-6959-3367"},"institutions":[{"id":"https://openalex.org/I31151848","display_name":"Technical University of Sofia","ror":"https://ror.org/052prhs50","country_code":"BG","type":"education","lineage":["https://openalex.org/I31151848"]}],"countries":["BG"],"is_corresponding":false,"raw_author_name":"Roumen Trifonov","raw_affiliation_strings":["Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Sofia,Dept. of Information Technology in Industry,Sofia,Bulgaria","institution_ids":["https://openalex.org/I31151848"]},{"raw_affiliation_string":"Dept. of Information Technology in Industry, Technical University of Sofia, Sofia, Bulgaria","institution_ids":["https://openalex.org/I31151848"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1098,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82097834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9965999722480774,"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":0.9965999722480774,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9623000025749207,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7663139700889587},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.7001789808273315},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6420053839683533},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6051317453384399},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5722060203552246},{"id":"https://openalex.org/keywords/connectionism","display_name":"Connectionism","score":0.5562178492546082},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5176251530647278},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5012962818145752},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.49233925342559814},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4716814160346985},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4437772035598755},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4373508095741272},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4150257408618927}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663139700889587},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.7001789808273315},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6420053839683533},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6051317453384399},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5722060203552246},{"id":"https://openalex.org/C8521452","wikidata":"https://www.wikidata.org/wiki/Q203790","display_name":"Connectionism","level":3,"score":0.5562178492546082},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5176251530647278},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5012962818145752},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.49233925342559814},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4716814160346985},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4437772035598755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4373508095741272},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4150257408618927},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/is57118.2022.10019673","is_oa":false,"landing_page_url":"https://doi.org/10.1109/is57118.2022.10019673","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 11th International Conference on Intelligent Systems (IS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1808591511","https://openalex.org/W2019598563","https://openalex.org/W2039573396","https://openalex.org/W2144276202","https://openalex.org/W2162635690","https://openalex.org/W2304531936","https://openalex.org/W2888850715","https://openalex.org/W4312750805","https://openalex.org/W6638671696"],"related_works":["https://openalex.org/W4205841273","https://openalex.org/W4205525690","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W2937099569","https://openalex.org/W3005992387","https://openalex.org/W4387250752"],"abstract_inverted_index":{"What":[0],"algorithms":[1,29],"to":[2,67,109,121,178,191],"choose":[3],"for":[4],"an":[5],"incremental,":[6],"predictive,":[7],"and":[8,13,19,23,31,52,81,101,138,161,166,188,197],"more":[9],"importantly,":[10],"explainable":[11,50],"learning":[12,54],"modelling":[14],"of":[15,43,49,113,152,158,171,185,201],"time":[16,25,35,117,186],"series":[17,36,118,187],"data,":[18,90],"specifically":[20],"\u2013":[21],"economic":[22],"financial":[24],"series?":[26],"Will":[27],"these":[28,114,153],"reveal":[30],"explain":[32],"abnormality":[33],"in":[34,46,73,147,164],"over":[37],"time?":[38],"This":[39],"problem":[40,163,174],"is":[41,116,175],"part":[42],"the":[44,47,68,74,92,111,133,142,148,159,162,202],"challenges":[45],"area":[48],"AI":[51],"life-long":[53],"systems.":[55],"Three":[56],"widely":[57],"used":[58,108],"evolving":[59],"connectionist":[60],"systems":[61],"(ECOS)":[62],"that":[63,86,150],"offer":[64],"a":[65,167,172,193,198],"solution":[66,170],"above":[69],"problems,":[70],"are":[71,83,145],"compared":[72],"paper.":[75],"The":[76,104],"first":[77],"two":[78],"models,":[79],"EFuNN":[80],"DENFIS,":[82],"neuro-fuzzy":[84],"models":[85],"deal":[87],"with":[88,99],"vector-based":[89],"while":[91],"spiking":[93],"neural":[94],"network":[95],"model":[96,169],"NeuCube":[97],"deals":[98],"temporal":[100],"spatio-temporal":[102],"data.":[103,203],"case":[105],"study":[106],"data":[107,119,160],"demonstrate":[110],"qualities":[112],"techniques":[115,154],"related":[120],"Bulgarian":[122],"petroleum":[123],"oil":[124],"imports":[125],"from":[126,141],"various":[127],"trading":[128],"partners.":[129],"Graphical":[130],"visualization":[131],"enhances":[132],"deep":[134],"analysis,":[135],"pattern":[136],"recognition,":[137],"knowledge":[139],"extraction":[140],"models.":[143],"Conclusions":[144],"drawn":[146],"sense":[149],"each":[151],"reveals":[155],"different":[156],"aspects":[157],"hand":[165],"single":[168],"complex":[173],"never":[176],"going":[177],"be":[179],"complete.":[180],"Future":[181],"work":[182],"outlines":[183],"integration":[184],"on-line":[189],"news":[190],"achieve":[192],"better":[194,199],"predictive":[195],"accuracy":[196],"understanding":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
