{"id":"https://openalex.org/W3081888420","doi":"https://doi.org/10.1109/icaci49185.2020.9177510","title":"Recurrent Restricted Boltzmann Machine for Chaotic Time-series Prediction","display_name":"Recurrent Restricted Boltzmann Machine for Chaotic Time-series Prediction","publication_year":2020,"publication_date":"2020-08-01","ids":{"openalex":"https://openalex.org/W3081888420","doi":"https://doi.org/10.1109/icaci49185.2020.9177510","mag":"3081888420"},"language":"en","primary_location":{"id":"doi:10.1109/icaci49185.2020.9177510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci49185.2020.9177510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 12th International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5002634184","display_name":"Ian Li","orcid":"https://orcid.org/0000-0002-1438-8830"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]},{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijie Li","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992","https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032636287","display_name":"Min Han","orcid":"https://orcid.org/0000-0002-2964-4884"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Han","raw_affiliation_strings":["Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384686","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-1305-5735"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]},{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992","https://openalex.org/I4210092944"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"471","issue":null,"first_page":"439","last_page":"445"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9968000054359436,"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":0.9968000054359436,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.9889000058174133,"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/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.8563145995140076},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7623265981674194},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6610182523727417},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.628045916557312},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6240315437316895},{"id":"https://openalex.org/keywords/chaotic","display_name":"Chaotic","score":0.5857999324798584},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5843622088432312},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.5611880421638489},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.551896870136261},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5001492500305176},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4434707462787628},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.375870019197464},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2300942838191986}],"concepts":[{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.8563145995140076},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7623265981674194},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6610182523727417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.628045916557312},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6240315437316895},{"id":"https://openalex.org/C2777052490","wikidata":"https://www.wikidata.org/wiki/Q5072826","display_name":"Chaotic","level":2,"score":0.5857999324798584},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5843622088432312},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.5611880421638489},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.551896870136261},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5001492500305176},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4434707462787628},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.375870019197464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2300942838191986},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaci49185.2020.9177510","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icaci49185.2020.9177510","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 12th International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W97016928","https://openalex.org/W1547224907","https://openalex.org/W1963812370","https://openalex.org/W1981364124","https://openalex.org/W2001263627","https://openalex.org/W2012743186","https://openalex.org/W2020572193","https://openalex.org/W2026430219","https://openalex.org/W2028379735","https://openalex.org/W2030486754","https://openalex.org/W2042492924","https://openalex.org/W2083022762","https://openalex.org/W2103496339","https://openalex.org/W2106595237","https://openalex.org/W2110485445","https://openalex.org/W2116064496","https://openalex.org/W2136922672","https://openalex.org/W2152254020","https://openalex.org/W2174574259","https://openalex.org/W2294916050","https://openalex.org/W2318004685","https://openalex.org/W2464909783","https://openalex.org/W2614198276","https://openalex.org/W2746162993","https://openalex.org/W2767894694","https://openalex.org/W2791210778","https://openalex.org/W2883439616","https://openalex.org/W2888109343","https://openalex.org/W2953450323","https://openalex.org/W2963122061","https://openalex.org/W2963446712","https://openalex.org/W3123995874","https://openalex.org/W3125965402","https://openalex.org/W4254816979","https://openalex.org/W6603960082","https://openalex.org/W6632924624","https://openalex.org/W6754107134"],"related_works":["https://openalex.org/W4283272532","https://openalex.org/W2952018105","https://openalex.org/W2119341610","https://openalex.org/W2916681395","https://openalex.org/W2556473569","https://openalex.org/W2193475944","https://openalex.org/W4302433642","https://openalex.org/W2529583158","https://openalex.org/W2108438604","https://openalex.org/W2551541394"],"abstract_inverted_index":{"How":[0],"to":[1,41,63,101,162],"extract":[2],"effective":[3],"information":[4,104,134,171,186],"from":[5,19],"large-scale":[6],"time-series":[7,34,47,56,65,141],"for":[8,51,76,140,168],"prediction":[9,48,86,108,182],"has":[10,29,130,180],"become":[11],"a":[12,60,72,95,111,131,146],"hot":[13],"topic":[14],"in":[15,33,172],"dynamic":[16,77,103,126],"modeling.":[17],"Benefiting":[18],"powerful":[20],"unsupervised":[21],"feature":[22,35,73,153,164],"learning":[23],"ability,":[24],"restricted":[25,97],"Boltzmann":[26,98],"machine":[27,99],"(RBM)":[28],"exhibited":[30],"fabulous":[31],"results":[32],"extraction,":[36],"and":[37,79,105,157,166,184],"is":[38,137,149],"more":[39,138],"adaptive":[40],"input":[42],"data":[43],"than":[44],"many":[45],"traditional":[46],"models.":[49],"However,":[50],"the":[52,82,125,152,169,173],"application":[53],"of":[54,84,90,114,155,160],"chaotic":[55],"prediction,":[57],"RBM":[58,69,156],"lacks":[59],"unique":[61],"mechanism":[62,75],"capture":[64,102],"information.":[66],"In":[67,88],"addition,":[68],"only":[70,122],"provides":[71],"extraction":[74],"modeling":[78],"cannot":[80],"perform":[81,106],"task":[83],"regression":[85,107],"alone.":[87],"view":[89],"aforementioned":[91],"problems,":[92],"we":[93],"propose":[94],"recurrent":[96,112,119,174],"(RRBM)":[100],"by":[109],"introducing":[110],"structure":[113,120],"leaky":[115],"integral":[116],"reservoir.":[117],"This":[118],"not":[121],"can":[123],"remedy":[124],"characteristics,":[127],"but":[128],"also":[129],"short-term":[132],"historical":[133],"memory,":[135],"which":[136],"suitable":[139],"applications.":[142],"On":[143],"this":[144],"basis,":[145],"cross-layer":[147],"connection":[148],"established":[150],"between":[151],"layer":[154,159],"output":[158],"RRBM":[161,179],"achieve":[163],"reuse":[165],"compensate":[167],"missing":[170],"process.":[175],"Experiments":[176],"show":[177],"that":[178],"smaller":[181],"error":[183],"higher":[185],"utilization.":[187]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}