{"id":"https://openalex.org/W4413392949","doi":"https://doi.org/10.23919/acc63710.2025.11108066","title":"Data-driven Koopman Operator-based Prediction and Control Using Model Averaging","display_name":"Data-driven Koopman Operator-based Prediction and Control Using Model Averaging","publication_year":2025,"publication_date":"2025-07-08","ids":{"openalex":"https://openalex.org/W4413392949","doi":"https://doi.org/10.23919/acc63710.2025.11108066"},"language":"en","primary_location":{"id":"doi:10.23919/acc63710.2025.11108066","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc63710.2025.11108066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 American Control Conference (ACC)","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/A5070518281","display_name":"Daisuke Uchida","orcid":"https://orcid.org/0000-0002-2809-2707"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Daisuke Uchida","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5035881605","display_name":"Karthik Duraisamy","orcid":"https://orcid.org/0000-0002-3519-8147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karthik Duraisamy","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5070518281"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8599,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92494601,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1083","last_page":"1088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.8442999720573425,"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":0.8442999720573425,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.7638999819755554,"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/computer-science","display_name":"Computer science","score":0.5934877991676331},{"id":"https://openalex.org/keywords/operator","display_name":"Operator (biology)","score":0.5752774477005005},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4168546199798584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5934877991676331},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.5752774477005005},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4168546199798584},{"id":"https://openalex.org/C86339819","wikidata":"https://www.wikidata.org/wiki/Q407384","display_name":"Transcription factor","level":3,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C158448853","wikidata":"https://www.wikidata.org/wiki/Q425218","display_name":"Repressor","level":4,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/acc63710.2025.11108066","is_oa":false,"landing_page_url":"https://doi.org/10.23919/acc63710.2025.11108066","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 American Control Conference (ACC)","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":24,"referenced_works":["https://openalex.org/W1591018827","https://openalex.org/W1990779154","https://openalex.org/W2030625232","https://openalex.org/W2061082730","https://openalex.org/W2158840489","https://openalex.org/W2281805729","https://openalex.org/W2561027863","https://openalex.org/W2605947465","https://openalex.org/W2782591075","https://openalex.org/W2789758093","https://openalex.org/W2948567396","https://openalex.org/W3099690969","https://openalex.org/W3118303791","https://openalex.org/W3140564639","https://openalex.org/W3142651044","https://openalex.org/W3194182445","https://openalex.org/W4205769419","https://openalex.org/W4210968171","https://openalex.org/W4239539940","https://openalex.org/W4382936193","https://openalex.org/W4386373863","https://openalex.org/W4399876261","https://openalex.org/W4400447134","https://openalex.org/W4409441673"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"This":[0],"work":[1],"presents":[2],"a":[3,10,60,68,79,110],"data-driven":[4,22,69],"Koopman":[5,16,75],"operator-based":[6],"modeling":[7,23,135],"method":[8,70],"using":[9,82],"model":[11,63,98,124,129,139],"averaging":[12,64],"technique.":[13],"While":[14],"the":[15,91,100,119,126,134,142],"operator":[17],"has":[18],"been":[19],"used":[20],"for":[21,109],"and":[24,39,50,85],"control":[25],"of":[26,52,90,93,113,128,137],"nonlinear":[27],"dynamics,":[28],"it":[29],"is":[30,102],"challenging":[31],"to":[32,46,66,105],"accurately":[33],"reconstruct":[34],"unknown":[35],"dynamics":[36],"from":[37,59],"data":[38],"perform":[40],"different":[41],"decision-making":[42],"tasks,":[43],"mainly":[44],"due":[45],"its":[47],"infinite":[48],"dimensionality":[49],"difficulty":[51],"finding":[53],"invariant":[54],"subspaces.":[55],"We":[56],"utilize":[57],"ideas":[58],"Bayesian":[61],"inference-based":[62],"technique":[65],"devise":[67],"that":[71,141],"first":[72],"populates":[73],"multiple":[74],"models":[76],"starting":[77],"with":[78],"feature":[80],"extraction":[81],"neural":[83],"networks":[84],"then":[86],"computes":[87],"point":[88],"estimates":[89],"posterior":[92],"predicted":[94],"variables.":[95],"Although":[96],"each":[97,138],"in":[99],"ensemble":[101,130],"not":[103],"likely":[104],"be":[106,146],"accurate":[107],"enough":[108],"wide":[111],"range":[112],"operating":[114],"points":[115],"or":[116],"unseen":[117],"data,":[118],"proposed":[120],"weighted":[121],"linear":[122],"embedding":[123],"combines":[125],"outputs":[127],"aiming":[131],"at":[132],"compensating":[133],"error":[136],"so":[140],"overall":[143],"performance":[144],"will":[145],"improved.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}