{"id":"https://openalex.org/W2897150198","doi":"https://doi.org/10.1145/3264746.3264753","title":"Dimensionality reduction by bayesian eigenvalue-analysis for state prediction in large sensor systems","display_name":"Dimensionality reduction by bayesian eigenvalue-analysis for state prediction in large sensor systems","publication_year":2018,"publication_date":"2018-10-09","ids":{"openalex":"https://openalex.org/W2897150198","doi":"https://doi.org/10.1145/3264746.3264753","mag":"2897150198"},"language":"en","primary_location":{"id":"doi:10.1145/3264746.3264753","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3264746.3264753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","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/A5053072850","display_name":"J\u00fcrgen Herp","orcid":"https://orcid.org/0000-0003-1799-8551"},"institutions":[{"id":"https://openalex.org/I177969490","display_name":"University of Southern Denmark","ror":"https://ror.org/03yrrjy16","country_code":"DK","type":"education","lineage":["https://openalex.org/I177969490"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"J\u00fcrgen Herp","raw_affiliation_strings":["University of Southern Denmark, Odense"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern Denmark, Odense","institution_ids":["https://openalex.org/I177969490"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065485055","display_name":"Esmaeil S. Nadimi","orcid":"https://orcid.org/0000-0003-2613-2696"},"institutions":[{"id":"https://openalex.org/I177969490","display_name":"University of Southern Denmark","ror":"https://ror.org/03yrrjy16","country_code":"DK","type":"education","lineage":["https://openalex.org/I177969490"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Esmaeil S. Nadimi","raw_affiliation_strings":["University of Southern Denmark, Odense"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Southern Denmark, Odense","institution_ids":["https://openalex.org/I177969490"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177969490"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12592169,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9934999942779541,"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/T12261","display_name":"Statistical Mechanics and Entropy","score":0.9933000206947327,"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/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.7308090925216675},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6605663299560547},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.629125714302063},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5983566641807556},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5614545345306396},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5536572933197021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5266499519348145},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48251602053642273},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.47638648748397827},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.4562760889530182},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.454296737909317},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.44450023770332336},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.41214632987976074},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3684201240539551},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36253029108047485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35025057196617126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2799171209335327},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19943949580192566}],"concepts":[{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.7308090925216675},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6605663299560547},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.629125714302063},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5983566641807556},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5614545345306396},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5536572933197021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5266499519348145},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48251602053642273},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.47638648748397827},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4562760889530182},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.454296737909317},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.44450023770332336},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.41214632987976074},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3684201240539551},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36253029108047485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35025057196617126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2799171209335327},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19943949580192566},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3264746.3264753","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3264746.3264753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:sdu.dk:openaire_cris_publications/5bd8d4d1-ccae-46a0-a6c9-a3a2340c9d6c","is_oa":false,"landing_page_url":"https://portal.findresearcher.sdu.dk/da/publications/5bd8d4d1-ccae-46a0-a6c9-a3a2340c9d6c","pdf_url":null,"source":{"id":"https://openalex.org/S4306400423","display_name":"University of Southern Denmark Research Portal (University of Southern Denmark)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177969490","host_organization_name":"University of Southern Denmark","host_organization_lineage":["https://openalex.org/I177969490"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Herp, J & S. Nadimi, E 2018, Dimensionality reduction by bayesian eigenvalue-analysis for state prediction in large sensor systems: with application in wind turbines. in Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems. Association for Computing Machinery, pp. 1-5, Conference on Research in Adaptive and Convergent Systems, Honolulu, Hawaii, United States, 09/10/2018. https://doi.org/10.1145/3264746.3264753","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.8999999761581421,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320323799","display_name":"Syddansk Universitet","ror":"https://ror.org/03yrrjy16"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W615589970","https://openalex.org/W1520752838","https://openalex.org/W1551952938","https://openalex.org/W1976750033","https://openalex.org/W1997494785","https://openalex.org/W2015245929","https://openalex.org/W2020856737","https://openalex.org/W2023124966","https://openalex.org/W2030629414","https://openalex.org/W2060581589","https://openalex.org/W2080031031","https://openalex.org/W2106084579","https://openalex.org/W2243654239","https://openalex.org/W2546831163","https://openalex.org/W2589218935","https://openalex.org/W2592806208","https://openalex.org/W2600602093","https://openalex.org/W2791604724","https://openalex.org/W3106227593","https://openalex.org/W3122232506","https://openalex.org/W4255194165"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"The":[0],"potential":[1],"of":[2,5,24,38,41,50,59,84,91],"the":[3,18,39,48,51,65,70,73,82,88,97,101],"theory":[4],"random":[6],"matrices":[7],"are":[8,94],"presented":[9],"and":[10,47,78,107],"evaluated":[11],"as":[12],"a":[13,22,42],"statistical":[14],"tool":[15],"to":[16],"represent":[17],"empirical":[19,52,79],"correlations":[20],"in":[21],"study":[23],"multivariate":[25],"time":[26,89],"series.":[27],"A":[28],"new":[29],"sub":[30],"space":[31],"state":[32,44,104],"prediction":[33,45,67,105],"framework":[34,99],"is":[35,76,108],"proposed,":[36],"consisting":[37],"combination":[40],"Bayesian":[43,103],"algorithm":[46,106],"eigenvalues":[49,85],"correlation":[53,74],"matrix.":[54],"In":[55],"an":[56],"industrial":[57],"use-case":[58],"wind":[60],"turbines,":[61],"remarkable":[62],"agreement":[63],"between":[64],"theoretical":[66],"(based":[68],"on":[69],"assumption":[71],"that":[72],"matrix":[75],"random)":[77],"data,":[80],"concerning":[81],"density":[83],"associated":[86],"with":[87],"series":[90],"different":[92],"sensors,":[93],"found.":[95],"Finally,":[96],"proposed":[98],"outperforms":[100],"existing":[102],"computationally":[109],"more":[110],"feasible":[111],"than":[112],"feeding":[113],"unprocessed":[114],"data.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
