{"id":"https://openalex.org/W1995930498","doi":"https://doi.org/10.1142/s0129065790000102","title":"PREDICTING THE FUTURE: A CONNECTIONIST APPROACH","display_name":"PREDICTING THE FUTURE: A CONNECTIONIST APPROACH","publication_year":1990,"publication_date":"1990-01-01","ids":{"openalex":"https://openalex.org/W1995930498","doi":"https://doi.org/10.1142/s0129065790000102","mag":"1995930498"},"language":"en","primary_location":{"id":"doi:10.1142/s0129065790000102","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065790000102","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"],"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/A5037027451","display_name":"Andreas S. Weigend","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas S. Weigend","raw_affiliation_strings":["Physics Department, Stanford University, Stanford, CA 94305, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physics Department, Stanford University, Stanford, CA 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114406750","display_name":"Bernardo A. Huberman","orcid":"https://orcid.org/0000-0002-6783-0864"},"institutions":[{"id":"https://openalex.org/I173498003","display_name":"Palo Alto Research Center","ror":"https://ror.org/0529fxt39","country_code":"US","type":"facility","lineage":["https://openalex.org/I173498003","https://openalex.org/I4210132870"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bernardo A. Huberman","raw_affiliation_strings":["Dynamics of Computation Group, Xerox PARC, Palo Alto, CA 94304, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dynamics of Computation Group, Xerox PARC, Palo Alto, CA 94304, USA","institution_ids":["https://openalex.org/I173498003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048240638","display_name":"David E. Rumelhart","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David E. Rumelhart","raw_affiliation_strings":["Psychology Department, Stanford University, Stanford, CA 94305, USA","Psychology department, Stanford University, Stanford, CA 94305, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Psychology Department, Stanford University, Stanford, CA 94305, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Psychology department, Stanford University, Stanford, CA 94305, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":48.6762,"has_fulltext":false,"cited_by_count":726,"citation_normalized_percentile":{"value":0.99905871,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":"01","issue":"03","first_page":"193","last_page":"209"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9825999736785889,"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":0.9825999736785889,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9724000096321106,"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"}},{"id":"https://openalex.org/T12261","display_name":"Statistical Mechanics and Entropy","score":0.939300000667572,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sigmoid-function","display_name":"Sigmoid function","score":0.8598071336746216},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7261930108070374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7239975333213806},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6372407078742981},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5633547306060791},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5342872142791748},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5257856845855713},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4457997679710388},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4128338694572449},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4040784239768982},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3885013461112976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2737666368484497}],"concepts":[{"id":"https://openalex.org/C81388566","wikidata":"https://www.wikidata.org/wiki/Q526668","display_name":"Sigmoid function","level":3,"score":0.8598071336746216},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7261930108070374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7239975333213806},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6372407078742981},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5633547306060791},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5342872142791748},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5257856845855713},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4457997679710388},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4128338694572449},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4040784239768982},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3885013461112976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2737666368484497},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0129065790000102","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065790000102","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"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2242271381","https://openalex.org/W2378555542","https://openalex.org/W1974708359","https://openalex.org/W2354237749","https://openalex.org/W2357809648","https://openalex.org/W2120909944","https://openalex.org/W2990514669","https://openalex.org/W2381291696","https://openalex.org/W2541528416","https://openalex.org/W2380779867"],"abstract_inverted_index":{"We":[0,16,97],"investigate":[1],"the":[2,9,30,58,70,79,82,95,117,123,132],"effectiveness":[3],"of":[4,12,22,43,50,61,78],"connectionist":[5],"architectures":[6],"for":[7,47,111],"predicting":[8],"future":[10],"behavior":[11],"nonlinear":[13,137],"dynamical":[14],"systems.":[15],"focus":[17],"on":[18],"real-world":[19],"time":[20,83],"series":[21,33],"limited":[23],"record":[24],"length.":[25],"Two":[26],"examples":[27],"are":[28,103],"analyzed:":[29],"benchmark":[31],"sunspot":[32],"and":[34,63,88],"chaotic":[35],"data":[36],"from":[37],"a":[38,66],"computational":[39],"ecosystem.":[40],"The":[41,76],"problem":[42],"overfitting,":[44],"particularly":[45],"serious":[46],"short":[48],"records":[49],"noisy":[51],"data,":[52],"is":[53,120],"addressed":[54],"both":[55],"by":[56,64],"using":[57],"statistical":[59,138],"method":[60],"validation":[62],"adding":[65],"complexity":[67],"term":[68],"to":[69,107],"cost":[71],"function":[72],"(\"back-propagation":[73],"with":[74,131],"weight-elimination\").":[75],"dimension":[77],"dynamics":[80],"underlying":[81],"series,":[84],"its":[85,89],"Liapunov":[86],"coefficient,":[87],"nonlinearity":[90],"can":[91],"be":[92],"determined":[93],"via":[94],"network.":[96],"also":[98],"show":[99],"why":[100],"sigmoid":[101,128],"units":[102],"superior":[104],"in":[105,122],"performance":[106],"radial":[108],"basis":[109],"functions":[110],"high-dimensional":[112],"input":[113],"spaces.":[114],"Furthermore,":[115],"since":[116],"ultimate":[118],"goal":[119],"accuracy":[121],"prediction,":[124],"we":[125],"find":[126],"that":[127],"networks":[129],"trained":[130],"weight-elimination":[133],"algorithm":[134],"outperform":[135],"traditional":[136],"approaches.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":20}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}