{"id":"https://openalex.org/W205463531","doi":null,"title":"An algorithm for the addition of time-delayed connections to recurrent neural networks.","display_name":"An algorithm for the addition of time-delayed connections to recurrent neural networks.","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W205463531","mag":"205463531"},"language":"en","primary_location":{"id":"mag:205463531","doi":null,"is_oa":false,"landing_page_url":"http://www.cs.montana.edu/~elser/ai_papers/An%20Algorithm%20for%20the%20Addition%20of%20Time-Delayed%20Connections%20to%20Recurrent%20Neural%20Networks.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421047","display_name":"The European Symposium on Artificial Neural Networks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"The European Symposium on Artificial Neural Networks","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5019399008","display_name":"Romuald Bon\u00e9","orcid":"https://orcid.org/0000-0002-0106-6576","observed_orcids":["https://orcid.org/0000-0002-0106-6576"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Romuald Bon\u00e9","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028132236","display_name":"Michel Crucianu","orcid":"https://orcid.org/0000-0001-8204-6843","observed_orcids":["https://orcid.org/0000-0001-8204-6843"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michel Crucianu","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-8204-6843","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111446435","display_name":"J. P. Asselin de Beauville","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I110017253","display_name":"Universit\u00e9 de Tours","ror":"https://ror.org/02wwzvj46","country_code":"FR","type":"education","lineage":["https://openalex.org/I110017253"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J. P. Asselin de Beauville","raw_affiliation_strings":["Fran\u00e7ois Rabelais University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fran\u00e7ois Rabelais University","institution_ids":["https://openalex.org/I110017253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"293","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9976000189781189,"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":0.9976000189781189,"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/T11347","display_name":"Neural Networks Stability and Synchronization","score":0.0010000000474974513,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/recurrent-neural-networks","display_name":"recurrent neural networks","score":0.9829999804496765},{"id":"https://openalex.org/keywords/time-series-modeling","display_name":"time series modeling","score":0.7379999756813049},{"id":"https://openalex.org/keywords/long-term-dependencies","display_name":"long-range dependencies","score":0.9879999756813049},{"id":"https://openalex.org/keywords/network-pruning","display_name":"network pruning","score":0.42100000381469727}],"concepts":[{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.8184875249862671},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6925475597381592},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6914845705032349},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5767903923988342},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.559106707572937},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5503734946250916},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4576003849506378},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4296058118343353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33160680532455444},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:205463531","doi":null,"is_oa":false,"landing_page_url":"http://www.cs.montana.edu/~elser/ai_papers/An%20Algorithm%20for%20the%20Addition%20of%20Time-Delayed%20Connections%20to%20Recurrent%20Neural%20Networks.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421047","display_name":"The European Symposium on Artificial Neural Networks","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"The European Symposium on Artificial Neural Networks","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1606326889","https://openalex.org/W1995930498","https://openalex.org/W2016589492","https://openalex.org/W2066366061","https://openalex.org/W2091054786","https://openalex.org/W2099257174","https://openalex.org/W2103452139","https://openalex.org/W2105727046","https://openalex.org/W2107878631","https://openalex.org/W2126456774","https://openalex.org/W2132107362","https://openalex.org/W2145739586","https://openalex.org/W2147413253","https://openalex.org/W2153827974","https://openalex.org/W2154642048","https://openalex.org/W2163899311","https://openalex.org/W2170852120","https://openalex.org/W2472864847"],"related_works":["https://openalex.org/W2083186188","https://openalex.org/W2096610921","https://openalex.org/W1891076495","https://openalex.org/W7132187481","https://openalex.org/W7100105437","https://openalex.org/W7096453680","https://openalex.org/W1555885222","https://openalex.org/W1994592287","https://openalex.org/W2072438838","https://openalex.org/W2145151144"],"abstract_inverted_index":{"Recurrent":[0],"neural":[1],"networks":[2],"possess":[3],"interesting":[4],"universal":[5],"approximation":[6],"capabilities,":[7],"making":[8],"them":[9],"good":[10,43,84],"candidates":[11],"for":[12,38,70],"time":[13,50],"series":[14],"modeling.":[15],"Unfortunately,":[16],"long":[17],"term":[18],"dependencies":[19],"are":[20,28],"difficult":[21],"to":[22,41,63,97],"learn":[23],"if":[24,45],"gradient":[25],"descent":[26],"algorithms":[27,40],"employed.":[29],"We":[30],"support":[31],"the":[32,53,65,88,94],"view":[33],"that":[34],"it":[35],"is":[36],"easier":[37],"these":[39],"find":[42],"solutions":[44],"one":[46,62],"includes":[47],"connections":[48,92],"with":[49],"delays":[51,69],"in":[52,93],"recurrent":[54,95],"networks.":[55],"The":[56],"algorithm":[57,81],"we":[58,74],"present":[59],"here":[60],"allows":[61],"choose":[64],"right":[66],"locations":[67],"and":[68],"such":[71],"connections.":[72],"As":[73],"show":[75],"on":[76],"two":[77],"benchmark":[78],"problems,":[79],"this":[80],"produces":[82],"very":[83],"results":[85],"while":[86],"keeping":[87],"total":[89],"number":[90],"of":[91],"network":[96],"a":[98],"minimum.":[99]},"counts_by_year":[],"updated_date":"2026-09-21T07:43:02.447757","created_date":"2016-06-24T00:00:00"}