{"id":"https://openalex.org/W4293766734","doi":"https://doi.org/10.1142/s0129065722500563","title":"Predicting a Time-Dependent Quantity Using Recursive Generative Query Network","display_name":"Predicting a Time-Dependent Quantity Using Recursive Generative Query Network","publication_year":2022,"publication_date":"2022-08-31","ids":{"openalex":"https://openalex.org/W4293766734","doi":"https://doi.org/10.1142/s0129065722500563","pmid":"https://pubmed.ncbi.nlm.nih.gov/36309813"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065722500563","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_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref","pubmed"],"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/A5062469834","display_name":"Grzegorz Miebs","orcid":"https://orcid.org/0000-0002-0628-6949"},"institutions":[{"id":"https://openalex.org/I46597724","display_name":"Pozna\u0144 University of Technology","ror":"https://ror.org/00p7p3302","country_code":"PL","type":"funder","lineage":["https://openalex.org/I46597724"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Grzegorz Miebs","raw_affiliation_strings":["Institute of Computing Science, Pozna\u0144 University of Technology, Piotrowo 2, 60-965 Pozna\u0144, Poland","PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]},{"raw_affiliation_string":"Institute of Computing Science, Pozna\u0144 University of Technology, Piotrowo 2, 60-965 Pozna\u0144, Poland","institution_ids":["https://openalex.org/I46597724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101839402","display_name":"Micha\u0142 W\u00f3jcik","orcid":"https://orcid.org/0000-0003-4299-9425"},"institutions":[{"id":"https://openalex.org/I46597724","display_name":"Pozna\u0144 University of Technology","ror":"https://ror.org/00p7p3302","country_code":"PL","type":"funder","lineage":["https://openalex.org/I46597724"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Micha\u0142 W\u00f3jcik","raw_affiliation_strings":["Institute of Computing Science, Pozna\u0144 University of Technology, Piotrowo 2, 60-965 Pozna\u0144, Poland","PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]},{"raw_affiliation_string":"Institute of Computing Science, Pozna\u0144 University of Technology, Piotrowo 2, 60-965 Pozna\u0144, Poland","institution_ids":["https://openalex.org/I46597724"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059618025","display_name":"Adam Karaszewski","orcid":null},"institutions":[],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Adam Karaszewski","raw_affiliation_strings":["PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025025567","display_name":"Ma\u0142gorzata Mochol-Grzelak","orcid":null},"institutions":[],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Ma\u0142gorzata Mochol-Grzelak","raw_affiliation_strings":["PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048464909","display_name":"Paulina Wawdysz","orcid":null},"institutions":[],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Paulina Wawdysz","raw_affiliation_strings":["PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022251442","display_name":"Rafa\u0142 A. Bachorz","orcid":"https://orcid.org/0000-0002-6940-9432"},"institutions":[{"id":"https://openalex.org/I4210124861","display_name":"Institute for Medical Biology","ror":"https://ror.org/02kstzn75","country_code":"PL","type":"funder","lineage":["https://openalex.org/I4210124861","https://openalex.org/I99542240"]},{"id":"https://openalex.org/I99542240","display_name":"Polish Academy of Sciences","ror":"https://ror.org/01dr6c206","country_code":"PL","type":"government","lineage":["https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Rafa\u0142 A. Bachorz","raw_affiliation_strings":["Institute of Medical Biology, Polish Academy of Sciences, Lodowa 103, 93-232 \u0141\u00f3d\u017a, Poland","PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland"],"affiliations":[{"raw_affiliation_string":"PSI Poland, Advanced Analytics Team, Towarowa 37, 61-896 Pozna\u0144, Poland","institution_ids":[]},{"raw_affiliation_string":"Institute of Medical Biology, Polish Academy of Sciences, Lodowa 103, 93-232 \u0141\u00f3d\u017a, Poland","institution_ids":["https://openalex.org/I4210124861","https://openalex.org/I99542240"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.163,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.356175,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":59,"max":69},"biblio":{"volume":"32","issue":"11","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9919,"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"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9919,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9913,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9904,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5596316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7903607},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6140404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.60718286},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5596316},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.547629},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5040168},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.50185823},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.490162},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45901504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4494946},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4180014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3346389},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":"","qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0129065722500563","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_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36309813","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":["National Institutes of Health"],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.53,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"grants":[{"funder":"https://openalex.org/F4320335039","funder_display_name":"Narodowe Centrum Bada\u0144 i Rozwoju","award_id":"POIR.01.01.01-00-0300/19."}],"datasets":[],"versions":[],"referenced_works_count":43,"referenced_works":["https://openalex.org/W1946238955","https://openalex.org/W1968398927","https://openalex.org/W1991151011","https://openalex.org/W1993260141","https://openalex.org/W2011301426","https://openalex.org/W2015028539","https://openalex.org/W2028612364","https://openalex.org/W2041253116","https://openalex.org/W2079309933","https://openalex.org/W2101227080","https://openalex.org/W2123513648","https://openalex.org/W2147350962","https://openalex.org/W2170362173","https://openalex.org/W2261040853","https://openalex.org/W2617614397","https://openalex.org/W2757751999","https://openalex.org/W2794022343","https://openalex.org/W2808492412","https://openalex.org/W2886910949","https://openalex.org/W2898456550","https://openalex.org/W2899818400","https://openalex.org/W2913408913","https://openalex.org/W2916071927","https://openalex.org/W2944758627","https://openalex.org/W2954043074","https://openalex.org/W2963073614","https://openalex.org/W2990138404","https://openalex.org/W3003648978","https://openalex.org/W3031087087","https://openalex.org/W3037331090","https://openalex.org/W3037485096","https://openalex.org/W3037916286","https://openalex.org/W3042758249","https://openalex.org/W3080798910","https://openalex.org/W3107324520","https://openalex.org/W3113483010","https://openalex.org/W3137749107","https://openalex.org/W3143873535","https://openalex.org/W3158666754","https://openalex.org/W3202342022","https://openalex.org/W4226157171","https://openalex.org/W4226178922","https://openalex.org/W4230515179"],"related_works":["https://openalex.org/W2990514669","https://openalex.org/W2883475164","https://openalex.org/W2393723963","https://openalex.org/W2381421930","https://openalex.org/W2378555542","https://openalex.org/W2363206876","https://openalex.org/W2357809648","https://openalex.org/W2242271381","https://openalex.org/W1632690555","https://openalex.org/W1629725936"],"abstract_inverted_index":{"We":[0],"propose":[1],"here":[2,39],"a":[3,32,106,184,233],"novel":[4],"neural":[5],"architecture":[6],"dedicated":[7],"to":[8,26,149,183,213],"the":[9,22,27,41,54,62,72,91,101,109,113,133,155,168,171,180,189,198,225],"prediction":[10,46,169],"of":[11,21,24,31,47,61,112,125,135,167,188,227],"time":[12,48,64,76,115,215],"series.":[13,49,116],"It":[14],"can":[15,193,208],"be":[16,194,209],"considered":[17],"as":[18,40],"an":[19,136],"adaptation":[20],"idea":[23,119],"(GQN)":[25],"data":[28,173],"which":[29,66],"is":[30,57,78,95,120,147,230],"sequence":[33,228],"nature.":[34],"The":[35,50,117,143,164,205],"new":[36],"approach,":[37],"dubbed":[38],"(RGQN),":[42],"allows":[43],"for":[44],"efficient":[45],"predictor":[51],"information":[52,192],"(i.e.":[53],"independent":[55],"variable)":[56],"one":[58],"or":[59],"more":[60],"other":[63,221],"series":[65,77,216],"are":[67],"in":[68,98,219],"some":[69],"relationship":[70],"with":[71,90,122,170],"predicted":[73,114],"sequence.":[74],"Each":[75],"accompanied":[79,231],"by":[80,232],"additional":[81],"meta-information":[82,104],"reflecting":[83,108],"its":[84],"selected":[85],"properties.":[86],"This":[87,191],"meta-information,":[88],"together":[89],"standard":[92],"dynamic":[93],"component,":[94],"provided":[96],"simultaneously":[97],"(RNN).":[99],"During":[100],"inference":[102],"phase,":[103],"becomes":[105],"query":[107],"expected":[110],"properties":[111],"proposed":[118],"illustrated":[121],"use":[123,222],"cases":[124,223],"strong":[126],"practical":[127],"relevance.":[128],"In":[129],"particular,":[130],"we":[131],"discuss":[132],"example":[134],"industrial":[137],"pipeline":[138],"that":[139,154],"transports":[140],"liquid":[141],"media.":[142],"trained":[144],"RGQN":[145,206],"model":[146],"applied":[148,195,210],"predict":[150],"pressure":[151,214],"signals,":[152],"assuming":[153],"training":[156],"was":[157],"carried":[158],"out":[159],"during":[160,179],"routine":[161],"operational":[162],"conditions.":[163],"subsequent":[165],"comparison":[166],"actual":[172],"gathered":[174],"under":[175],"extraordinary":[176],"circumstances,":[177],"e.g.":[178],"leakage,":[181],"leads":[182],"specific":[185],"residual":[186],"distribution":[187],"prediction.":[190],"directly":[196],"within":[197],"data-driven":[199],"Leak":[200],"Detection":[201],"and":[202],"Location":[203],"framework.":[204],"approach":[207],"not":[211],"only":[212],"but":[217],"also":[218],"many":[220],"where":[224],"quantity":[226],"nature":[229],"meta-descriptor.":[234]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4293766734","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-03-22T06:18:37.475187","created_date":"2022-08-31"}