{"id":"https://openalex.org/W4416250209","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228258","title":"A Study on Quantum Reservoir Recurrent Models for Time-Constrained Volatile Sequence Forecasting","display_name":"A Study on Quantum Reservoir Recurrent Models for Time-Constrained Volatile Sequence Forecasting","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250209","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228258"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5052397999","display_name":"Antonello Rosato","orcid":"https://orcid.org/0000-0002-4371-5925"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Antonello Rosato","raw_affiliation_strings":["University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184"],"affiliations":[{"raw_affiliation_string":"University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013731301","display_name":"Andrea Ceschini","orcid":"https://orcid.org/0000-0003-0555-9543"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Ceschini","raw_affiliation_strings":["University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184"],"affiliations":[{"raw_affiliation_string":"University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050693707","display_name":"Federico Succetti","orcid":"https://orcid.org/0000-0003-1207-9417"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federico Succetti","raw_affiliation_strings":["University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184"],"affiliations":[{"raw_affiliation_string":"University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021414038","display_name":"Samuel Yen-Chi Chen","orcid":"https://orcid.org/0000-0003-0114-4826"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuel Yen-Chi Chen","raw_affiliation_strings":["Wells Fargo,New York,NY,U.S.A"],"affiliations":[{"raw_affiliation_string":"Wells Fargo,New York,NY,U.S.A","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015796693","display_name":"Massimo Panella","orcid":"https://orcid.org/0000-0002-9876-1494"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Massimo Panella","raw_affiliation_strings":["University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184"],"affiliations":[{"raw_affiliation_string":"University of Rome \"La Sapienza\",Electronics and Telecommunications (DIET),Department of Information Engineering,Rome,Italy,00184","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052397999"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":null,"apc_paid":null,"fwci":2.4253,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92042767,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.2985999882221222,"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":0.2985999882221222,"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/T10682","display_name":"Quantum Computing Algorithms and Architecture","score":0.23579999804496765,"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":0.10700000077486038,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reservoir-computing","display_name":"Reservoir computing","score":0.751800000667572},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.5288000106811523},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4975999891757965},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.3984000086784363},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.39820000529289246},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.39480000734329224},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.39320001006126404},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.38989999890327454}],"concepts":[{"id":"https://openalex.org/C135796866","wikidata":"https://www.wikidata.org/wiki/Q7315328","display_name":"Reservoir computing","level":4,"score":0.751800000667572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6718999743461609},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.5288000106811523},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3984000086784363},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.39820000529289246},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.39480000734329224},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.35510000586509705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35359999537467957},{"id":"https://openalex.org/C2778668878","wikidata":"https://www.wikidata.org/wiki/Q6380338","display_name":"Reservoir simulation","level":2,"score":0.3418999910354614},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.34119999408721924},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3075000047683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30640000104904175},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.26840001344680786},{"id":"https://openalex.org/C3020136221","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time sequence","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C14641988","wikidata":"https://www.wikidata.org/wiki/Q7315329","display_name":"Reservoir modeling","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C183250156","wikidata":"https://www.wikidata.org/wiki/Q5916050","display_name":"Reservoir engineering","level":3,"score":0.2524000108242035}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1757944","is_oa":false,"landing_page_url":"https://hdl.handle.net/11573/1757944","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W2064675550","https://openalex.org/W2157331557","https://openalex.org/W3045093737","https://openalex.org/W3082455048","https://openalex.org/W3083383871","https://openalex.org/W3118233967","https://openalex.org/W3132491925","https://openalex.org/W3148590207","https://openalex.org/W3207377511","https://openalex.org/W4312154946","https://openalex.org/W4312588299","https://openalex.org/W4321615273","https://openalex.org/W4372259985","https://openalex.org/W4383225765","https://openalex.org/W4384471097","https://openalex.org/W4385170715","https://openalex.org/W4385245566","https://openalex.org/W4385261005","https://openalex.org/W4386573663","https://openalex.org/W4392523455","https://openalex.org/W4400463031","https://openalex.org/W4401448089","https://openalex.org/W4402618489","https://openalex.org/W4403979930","https://openalex.org/W4404375569","https://openalex.org/W4407537873","https://openalex.org/W4408004960","https://openalex.org/W4408107795","https://openalex.org/W4408167059","https://openalex.org/W4408600405"],"related_works":[],"abstract_inverted_index":{"This":[0,105],"paper":[1],"investigates":[2],"the":[3,25,40,69,81,93,100,110,113,119,152,162,178,188],"potential":[4,163],"of":[5,56,112,154,164],"quantum-enhanced":[6,194],"models":[7,166],"for":[8,102,134,190],"time":[9,15,57,129],"series":[10],"forecasting":[11,136,195],"in":[12,54,65,92,171,193],"environments":[13],"where":[14],"is":[16,22],"a":[17,62,144],"fundamental":[18],"constraint.":[19],"The":[20,47,138],"focus":[21],"on":[23,24,143],"quantum":[26,72,165,199],"long":[27],"short":[28],"term":[29],"memory":[30],"networks":[31],"with":[32,123,158],"reservoir":[33,94,203],"(QR-LSTM),":[34],"and":[35,58,149,184,201],"our":[36],"proposed":[37],"novel":[38],"extension,":[39],"Autoencoded":[41],"Quantum":[42],"Reservoir":[43],"LSTM":[44,73],"Model":[45],"(QR-LSTM-AE).":[46],"QR-LSTM,":[48],"while":[49],"offering":[50],"substantial":[51],"computational":[52,120,159,185],"benefits":[53],"terms":[55],"resource":[59],"efficiency,":[60,160,186],"incurs":[61],"slight":[63],"decrease":[64],"performance":[66,90],"relative":[67],"to":[68,88,125,167],"fully":[70],"trainable":[71],"model.":[74],"To":[75],"address":[76],"this":[77],"trade-off,":[78],"we":[79],"introduce":[80],"QR-LSTM-AE,":[82],"which":[83],"utilizes":[84],"an":[85],"autoencoder-based":[86],"strategy":[87],"recover":[89],"lost":[91],"alone,":[95],"achieving":[96],"superior":[97],"accuracy":[98,157,183],"without":[99],"need":[101],"full":[103],"retraining.":[104],"approach":[106],"not":[107],"only":[108],"maintains":[109],"efficiency":[111],"QR-LSTM":[114],"but":[115],"also":[116],"significantly":[117],"reduces":[118],"cost":[121],"associated":[122],"adapting":[124],"new":[126],"data":[127],"or":[128],"series,":[130],"making":[131],"it":[132],"ideal":[133],"real-time":[135],"applications.":[137],"experiments":[139],"are":[140],"carried":[141],"out":[142],"energy-related,":[145],"highly":[146],"volatile":[147],"dataset,":[148],"results":[150],"underscore":[151],"importance":[153],"balancing":[155],"predictive":[156,182],"highlighting":[161],"offer":[168],"practical":[169],"solutions":[170],"time-constrained":[172],"environments.":[173],"Our":[174],"findings":[175],"demonstrate":[176],"that":[177],"QR-LSTM-AE":[179],"effectively":[180],"balances":[181],"paving":[187],"way":[189],"future":[191],"advancements":[192],"through":[196],"self-adaptive":[197],"models,":[198],"autoencoders,":[200],"attention-based":[202],"computing.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-11-14T00:00:00"}