{"id":"https://openalex.org/W2154965898","doi":"https://doi.org/10.1109/ijcnn.2007.4371283","title":"Forecasting the Unknown Dynamics in NN3 Database Using a Nonlinear Autoregressive Recurrent Neural Network","display_name":"Forecasting the Unknown Dynamics in NN3 Database Using a Nonlinear Autoregressive Recurrent Neural Network","publication_year":2007,"publication_date":"2007-08-01","ids":{"openalex":"https://openalex.org/W2154965898","doi":"https://doi.org/10.1109/ijcnn.2007.4371283","mag":"2154965898"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2007.4371283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371283","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","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/A5003846335","display_name":"Ehsan Safavieh","orcid":"https://orcid.org/0000-0002-9465-9468"},"institutions":[{"id":"https://openalex.org/I248924554","display_name":"Iran National Science Foundation","ror":"https://ror.org/03sr1ma14","country_code":"IR","type":"facility","lineage":["https://openalex.org/I248924554"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"E. Safavieh","raw_affiliation_strings":["SRRF, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"SRRF, Tehran, Iran","institution_ids":["https://openalex.org/I248924554"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076258547","display_name":"S. Andalib","orcid":null},"institutions":[{"id":"https://openalex.org/I248924554","display_name":"Iran National Science Foundation","ror":"https://ror.org/03sr1ma14","country_code":"IR","type":"facility","lineage":["https://openalex.org/I248924554"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"S. Andalib","raw_affiliation_strings":["SRRF, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"SRRF, Tehran, Iran","institution_ids":["https://openalex.org/I248924554"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005120711","display_name":"Arash Andalib","orcid":"https://orcid.org/0000-0002-7005-873X"},"institutions":[{"id":"https://openalex.org/I248924554","display_name":"Iran National Science Foundation","ror":"https://ror.org/03sr1ma14","country_code":"IR","type":"facility","lineage":["https://openalex.org/I248924554"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"A. Andalib","raw_affiliation_strings":["SRRF, Tehran, Iran"],"affiliations":[{"raw_affiliation_string":"SRRF, Tehran, Iran","institution_ids":["https://openalex.org/I248924554"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003846335"],"corresponding_institution_ids":["https://openalex.org/I248924554"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.25761204,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"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":0.9944000244140625,"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":0.9944000244140625,"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/T10244","display_name":"Chaos control and synchronization","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9728000164031982,"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/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.9757531881332397},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.9191814661026001},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6794427633285522},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6642627716064453},{"id":"https://openalex.org/keywords/star-model","display_name":"STAR model","score":0.6576137542724609},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6487423777580261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.644108772277832},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6000851392745972},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5926769375801086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4894517958164215},{"id":"https://openalex.org/keywords/setar","display_name":"SETAR","score":0.43945321440696716},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4198121726512909},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4196823239326477},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.4105515778064728},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4092874228954315},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33204385638237},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22384759783744812},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.20519864559173584}],"concepts":[{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.9757531881332397},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.9191814661026001},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6794427633285522},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6642627716064453},{"id":"https://openalex.org/C194657046","wikidata":"https://www.wikidata.org/wiki/Q7394685","display_name":"STAR model","level":4,"score":0.6576137542724609},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6487423777580261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.644108772277832},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6000851392745972},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5926769375801086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4894517958164215},{"id":"https://openalex.org/C30795276","wikidata":"https://www.wikidata.org/wiki/Q7389877","display_name":"SETAR","level":5,"score":0.43945321440696716},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4198121726512909},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4196823239326477},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.4105515778064728},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4092874228954315},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33204385638237},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22384759783744812},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.20519864559173584},{"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},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2007.4371283","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371283","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.295.889","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.295.889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.neural-forecasting-competition.com/downloads/NN3/methods/16-NN3_safavieh.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1981332527","https://openalex.org/W2031365860","https://openalex.org/W2033410765","https://openalex.org/W2035740143","https://openalex.org/W2040704490","https://openalex.org/W2103452139","https://openalex.org/W2107878631","https://openalex.org/W2121594221","https://openalex.org/W2124776405","https://openalex.org/W2313953460","https://openalex.org/W6678851513"],"related_works":["https://openalex.org/W4320078083","https://openalex.org/W2984112945","https://openalex.org/W1988789713","https://openalex.org/W1611117054","https://openalex.org/W4238343629","https://openalex.org/W2019155478","https://openalex.org/W3123153965","https://openalex.org/W2111126525","https://openalex.org/W4287185323","https://openalex.org/W4366145459"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,26,68],"nonlinear":[4,77],"autoregressive":[5,78],"(NAR)":[6],"recurrent":[7,72,107],"neural":[8,73],"network":[9],"is":[10,51,63,98],"used":[11],"for":[12,114],"the":[13,16,40,60,76,85,101,123,127,141],"prediction":[14],"of":[15,21,28,44,71,110,126],"next":[17],"18":[18],"data":[19,45],"samples":[20],"each":[22],"time":[23,120,129],"series":[24,130],"in":[25,32,64,119],"set":[27],"11":[29],"unknown":[30],"dynamics":[31],"NN3":[33],"Database.":[34],"The":[35],"models":[36],"are":[37,131],"built":[38],"on":[39,140],"reconstructed":[41],"state":[42],"spaces":[43],"and":[46,104],"no":[47,135],"other":[48,106],"domain":[49],"knowledge":[50],"available":[52,87,133],"to":[53,67,100],"be":[54],"used.":[55],"Here,":[56],"we":[57,92],"clarify":[58],"that":[59,95],"employed":[61],"method":[62],"part":[65],"similar":[66],"superior":[69],"subclass":[70],"network,":[74],"namely":[75],"model":[79,97],"with":[80],"exogenous":[81],"inputs":[82],"(NARX).":[83],"Using":[84],"extensive":[86],"research":[88],"about":[89],"NARX":[90],"networks,":[91],"briefly":[93],"explain":[94],"our":[96],"preferred":[99],"both":[102],"non-recursive":[103],"even":[105],"predictors,":[108],"because":[109],"its":[111],"intrinsic":[112],"ability":[113],"learning":[115],"long":[116],"term":[117],"dependencies":[118],"series.":[121],"As":[122],"desired":[124],"values":[125],"predicted":[128],"not":[132],"yet,":[134],"analysis":[136],"have":[137],"been":[138],"performed":[139],"presented":[142],"results.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
