{"id":"https://openalex.org/W6908383875","doi":"https://doi.org/10.25819/ubsi/10164","title":"Machine learning with nonlinear state space models","display_name":"Machine learning with nonlinear state space models","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6908383875","doi":"https://doi.org/10.25819/ubsi/10164"},"language":"en","primary_location":{"id":"doi:10.25819/ubsi/10164","is_oa":true,"landing_page_url":"https://doi.org/10.25819/ubsi/10164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400802","display_name":"Recherche und Kataloge (Universit\u00e4tsbibliothek Siegen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I206895457","host_organization_name":"University of Siegen","host_organization_lineage":["https://openalex.org/I206895457"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.25819/ubsi/10164","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sch\u00fcssler, Max","orcid":"https://orcid.org/0000-0003-0394-1693"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sch\u00fcssler, Max","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0394-1693","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"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":0,"citation_normalized_percentile":{"value":0.25673119,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.27399998903274536,"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/T12676","display_name":"Machine Learning and ELM","score":0.27399998903274536,"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/T10320","display_name":"Neural Networks and Applications","score":0.08510000258684158,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.0771000012755394,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6201000213623047},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.5940999984741211},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5430999994277954},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4932999908924103},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4611000120639801},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4528999924659729},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.44920000433921814},{"id":"https://openalex.org/keywords/nonlinear-autoregressive-exogenous-model","display_name":"Nonlinear autoregressive exogenous model","score":0.4336000084877014},{"id":"https://openalex.org/keywords/nonlinear-system-identification","display_name":"Nonlinear system identification","score":0.4221999943256378},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4088999927043915}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6410999894142151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230000257492065},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6201000213623047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6046000123023987},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.5940999984741211},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5430999994277954},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4611000120639801},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.44920000433921814},{"id":"https://openalex.org/C42536954","wikidata":"https://www.wikidata.org/wiki/Q7049462","display_name":"Nonlinear autoregressive exogenous model","level":3,"score":0.4336000084877014},{"id":"https://openalex.org/C22157029","wikidata":"https://www.wikidata.org/wiki/Q17080460","display_name":"Nonlinear system identification","level":4,"score":0.4221999943256378},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4088999927043915},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.382099986076355},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.3515999913215637},{"id":"https://openalex.org/C28704281","wikidata":"https://www.wikidata.org/wiki/Q180165","display_name":"Mechatronics","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C52918065","wikidata":"https://www.wikidata.org/wiki/Q230945","display_name":"State-space representation","level":2,"score":0.3125},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.29670000076293945},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C36299963","wikidata":"https://www.wikidata.org/wiki/Q1369844","display_name":"Observability","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C76956256","wikidata":"https://www.wikidata.org/wiki/Q27610560","display_name":"Process modeling","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.2599000036716461},{"id":"https://openalex.org/C2984755018","wikidata":"https://www.wikidata.org/wiki/Q17118374","display_name":"Nonlinear model","level":3,"score":0.2547999918460846},{"id":"https://openalex.org/C76969082","wikidata":"https://www.wikidata.org/wiki/Q486902","display_name":"Mathematical model","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.25819/ubsi/10164","is_oa":true,"landing_page_url":"https://doi.org/10.25819/ubsi/10164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400802","display_name":"Recherche und Kataloge (Universit\u00e4tsbibliothek Siegen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I206895457","host_organization_name":"University of Siegen","host_organization_lineage":["https://openalex.org/I206895457"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.25819/ubsi/10164","is_oa":true,"landing_page_url":"https://doi.org/10.25819/ubsi/10164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400802","display_name":"Recherche und Kataloge (Universit\u00e4tsbibliothek Siegen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I206895457","host_organization_name":"University of Siegen","host_organization_lineage":["https://openalex.org/I206895457"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Contemporary":[0],"automation":[1],"systems":[2],"require":[3],"accurate":[4,89],"models":[5,19,49,77,90,116,140,192,209],"for":[6,61,88,111,177],"analysis,":[7],"design,":[8],"and":[9,96,107,123,153,167,173,185,204,215,269,278],"control.":[10],"Oftentimes,":[11],"it":[12],"is":[13,24,39,57,117,127,148,223,233,239,261],"not":[14],"possible":[15],"to":[16,188],"derive":[17],"satisfactory":[18],"by":[20,79,85,252],"first":[21],"principles.":[22],"This":[23],"often":[25],"the":[26,36,44,74,80,86,94,124,199,231,242],"case":[27],"in":[28,32,70,98],"process":[29,38],"engineering":[30],"or":[31,43,272],"mechatronic":[33],"systems,":[34],"where":[35],"overall":[37,227],"just":[40,51],"too":[41,53],"complex,":[42],"development":[45],"of":[46,76,82,104,230,250,280],"those":[47],"first-principle":[48],"would":[50],"be":[52],"expensive.":[54],"Thus,":[55],"there":[56,66],"a":[58,101,151,160,216,247],"strong":[59],"demand":[60],"data-driven":[62,113],"modeling":[63],"approaches.":[64],"Additionally,":[65],"are":[67,193,210,282],"enormous":[68],"successes":[69,95],"machine":[71,99],"learning":[72],"concerning":[73],"generation":[75],"solely":[78],"use":[81],"data.":[83],"Driven":[84],"need":[87],"as":[91,93,150],"well":[92],"advances":[97],"learning,":[100],"novel":[102],"class":[103],"model":[105,126,130,143,246],"structures":[106,222],"associated":[108],"training":[109],"algorithms":[110,268],"building":[112],"nonlinear":[114,137,189,265],"dynamic":[115],"developed.":[118],"The":[119,146,226,259,275],"new":[120],"identification":[121,267],"procedure":[122],"resulting":[125],"called":[128],"local":[129,142],"state":[131,138,190],"space":[132,139,191],"network":[133],"(LMSSN).":[134],"It":[135,238],"fuses":[136],"with":[141,156],"networks":[144,183],"(LMNs).":[145],"LMSSN":[147,232,243,260,281],"designed":[149],"user-friendly":[152],"deterministic":[154],"approach":[155],"warm-start":[157],"initialization":[158],"(with":[159],"linear":[161],"model),":[162],"incrementally":[163],"growing":[164],"complexity,":[165],"favorable":[166],"robust":[168],"extrapolation":[169],"behavior,":[170],"easy":[171],"interpretation,":[172],"straightforward":[174],"incorporation":[175],"possibilities":[176],"prior":[178],"knowledge.":[179],"Furthermore,":[180],"recurrent":[181,206],"neural":[182],"(RNNs)":[184],"their":[186],"similarities":[187],"elaborated":[194],"on.":[195],"Popular":[196],"RNNs":[197],"like":[198],"long":[200],"short-term":[201],"memory":[202],"(LSTM)":[203],"gated":[205],"unit":[207],"(GRU)":[208],"translated":[211],"into":[212],"controls":[213],"perspective":[214],"comprehensive":[217],"study":[218],"comparing":[219],"different":[220],"RNN":[221],"carried":[224],"out.":[225],"outstanding":[228],"performance":[229],"demonstrated":[234,284],"on":[235,285],"various":[236],"applications.":[237],"shown":[240],"that":[241],"can":[244],"accurately":[245],"wide":[248],"variety":[249],"processes":[251],"consistently":[253],"computing":[254],"expressive":[255],"yet":[256],"compact":[257],"models.":[258],"benchmarked":[262],"against":[263],"state-of-the-art":[264],"system":[266],"achieves":[270],"similar":[271],"superior":[273],"results.":[274],"practical":[276],"usefulness":[277],"applicability":[279],"strikingly":[283],"two":[286],"real-world":[287],"processes.":[288]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}