{"id":"https://openalex.org/W2783009972","doi":"https://doi.org/10.1109/cdc.2017.8263890","title":"On the transient performance of Monte Carlo simulations for initial uncertainty forecasting","display_name":"On the transient performance of Monte Carlo simulations for initial uncertainty forecasting","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783009972","doi":"https://doi.org/10.1109/cdc.2017.8263890","mag":"2783009972"},"language":"en","primary_location":{"id":"doi:10.1109/cdc.2017.8263890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2017.8263890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 56th Annual Conference on Decision and Control (CDC)","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/A5101767237","display_name":"Chao Yang","orcid":"https://orcid.org/0000-0001-8272-3576"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chao Yang","raw_affiliation_strings":["graduate student of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"graduate student of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073597636","display_name":"Mrinal Kumar","orcid":"https://orcid.org/0000-0001-9747-9449"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mrinal Kumar","raw_affiliation_strings":["Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101767237"],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20027013,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1669","last_page":"1674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13126","display_name":"Scientific Research and Discoveries","score":0.9887999892234802,"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"}},{"id":"https://openalex.org/T11371","display_name":"Wind and Air Flow Studies","score":0.9843999743461609,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6985846757888794},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6390024423599243},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5925657749176025},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.5690258741378784},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5525847673416138},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5039963126182556},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.49548017978668213},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.456277996301651},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.43541383743286133},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.41840818524360657},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3692569136619568},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3526362180709839},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2222578525543213},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18933719396591187},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15786650776863098},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.12043163180351257},{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.09394127130508423}],"concepts":[{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6985846757888794},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6390024423599243},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5925657749176025},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5690258741378784},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5525847673416138},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5039963126182556},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.49548017978668213},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.456277996301651},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.43541383743286133},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.41840818524360657},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3692569136619568},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3526362180709839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2222578525543213},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18933719396591187},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15786650776863098},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.12043163180351257},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.09394127130508423},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cdc.2017.8263890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cdc.2017.8263890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 56th Annual Conference on Decision and Control (CDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W95577512","https://openalex.org/W130710483","https://openalex.org/W135467536","https://openalex.org/W621546036","https://openalex.org/W1483307070","https://openalex.org/W1513008779","https://openalex.org/W1527031437","https://openalex.org/W1975345292","https://openalex.org/W1987451306","https://openalex.org/W2009104157","https://openalex.org/W2016398076","https://openalex.org/W2063997360","https://openalex.org/W2110419110","https://openalex.org/W2134066908","https://openalex.org/W2154998879","https://openalex.org/W2155075984","https://openalex.org/W2317908795","https://openalex.org/W3020882730","https://openalex.org/W3141151088","https://openalex.org/W3175695286","https://openalex.org/W4232399354","https://openalex.org/W4240788980"],"related_works":["https://openalex.org/W2126907425","https://openalex.org/W2208639223","https://openalex.org/W2114656557","https://openalex.org/W1499764293","https://openalex.org/W2195963939","https://openalex.org/W2514372983","https://openalex.org/W4245379261","https://openalex.org/W2075503097","https://openalex.org/W1497303808","https://openalex.org/W4226314133"],"abstract_inverted_index":{"The":[0,28],"objective":[1],"of":[2,11,26,48,65,76,86,118,151],"this":[3,20,55],"paper":[4],"is":[5,31,60,90,93,114,130],"to":[6,141],"evaluate":[7],"the":[8,12,37,49,57,63,70,74,77,84,109,115,119],"transient":[9],"performance":[10],"conventional":[13],"Monte":[14],"Carlo":[15],"method":[16],"(called":[17],"FMC":[18,39,71,87,121],"in":[19,100],"paper)":[21],"with":[22,98,134],"a":[23,45,66],"fixed":[24],"number":[25],"samples.":[27],"following":[29],"question":[30],"asked:":[32],"under":[33],"what":[34],"conditions":[35],"could":[36],"propagated":[38,58,120],"ensemble":[40,59,146],"have":[41],"been":[42],"generated":[43],"by":[44],"direct":[46],"sampling":[47],"unknown":[50],"true":[51,110],"state-pdf?":[52],"To":[53],"answer":[54],"question,":[56],"viewed":[61],"as":[62,73],"realization":[64],"Markov":[67],"chain":[68],"and":[69],"process":[72],"evolution":[75,85],"associated":[78],"transition":[79,88,122],"kernel.":[80],"An":[81],"equation":[82],"governing":[83],"kernel":[89,123],"derived.":[91],"It":[92],"shown":[94],"that":[95],"for":[96,132,148],"systems":[97,133],"\u201czero-divergence\u201d":[99],"their":[101],"force":[102],"field":[103],"(\u2207":[104],"\u00b7":[105],"f":[106],"=":[107],"0),":[108],"evolved":[111],"state":[112],"pdf":[113],"invariant":[116],"distribution":[117],"at":[124],"all":[125],"times.":[126],"No":[127],"such":[128],"equivalence":[129],"guaranteed":[131],"non-zero":[135],"divergence.":[136],"Numerical":[137],"simulations":[138],"are":[139],"provided":[140],"support":[142],"theoretical":[143],"claims":[144],"about":[145],"quality":[147],"both":[149],"types":[150],"dynamic":[152],"systems.":[153]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}