{"id":"https://openalex.org/W4251081610","doi":"https://doi.org/10.1109/wsc.2016.7822114","title":"Brawler to CFAM: Incorporating stochastic engagement-level data in deterministic campaign models","display_name":"Brawler to CFAM: Incorporating stochastic engagement-level data in deterministic campaign models","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W4251081610","doi":"https://doi.org/10.1109/wsc.2016.7822114"},"language":"en","primary_location":{"id":"doi:10.1109/wsc.2016.7822114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2016.7822114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Winter Simulation Conference (WSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5088337167","display_name":"Benjamin R. Mayo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benjamin R. Mayo","raw_affiliation_strings":["Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069401578","display_name":"Todd J. Paciencia","orcid":"https://orcid.org/0000-0003-3703-1559"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Todd J. Paciencia","raw_affiliation_strings":["Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066554190","display_name":"Daniel P. Croghan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel P. Croghan","raw_affiliation_strings":["Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Headquarters, Air Force Studies, Analyses, and Assessments (AF/A9) Pentagon, Washington, DC, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3548,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61259338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"1","issue":null,"first_page":"484","last_page":"489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9697999954223633,"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"}},"topics":[{"id":"https://openalex.org/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9697999954223633,"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/T10557","display_name":"Social Media and Politics","score":0.9485999941825867,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.7102742195129395},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5308091640472412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5140601396560669},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4288698434829712},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37595391273498535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18542993068695068},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14708316326141357}],"concepts":[{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.7102742195129395},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5308091640472412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5140601396560669},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4288698434829712},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37595391273498535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18542993068695068},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14708316326141357},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wsc.2016.7822114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wsc.2016.7822114","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 Winter Simulation Conference (WSC)","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":6,"referenced_works":["https://openalex.org/W1585610988","https://openalex.org/W2107958340","https://openalex.org/W2165232124","https://openalex.org/W2517337901","https://openalex.org/W4256495360","https://openalex.org/W6635035540"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1534274833","https://openalex.org/W3117246195","https://openalex.org/W2081850291","https://openalex.org/W156620619","https://openalex.org/W2914363205","https://openalex.org/W1598221548","https://openalex.org/W1963695443","https://openalex.org/W2997844990"],"abstract_inverted_index":{"Headquarters":[0],"Air":[1,43],"Force":[2,9,44],"Studies,":[3],"Analyses,":[4],"and":[5,105,138],"Assessments":[6],"(AF/A9)":[7],"supports":[8],"Structure":[10],"decisions":[11],"by":[12,86,109],"integrating":[13],"analysis":[14,137],"at":[15],"various":[16],"levels":[17],"of":[18,112],"resolution.":[19],"The":[20],"Combat":[21],"Forces":[22],"Assessment":[23],"Model":[24],"(CFAM),":[25],"is":[26,47,67],"a":[27,48],"mixed":[28],"integer":[29],"program":[30],"incorporating":[31],"results":[32],"from":[33,72],"higher-resolution":[34],"models":[35,54],"to":[36],"identify":[37],"an":[38],"optimal":[39],"force":[40],"mix":[41],"within":[42],"resources.":[45],"CFAM":[46,77,126],"deterministic":[49],"model,":[50],"but":[51],"some":[52],"input":[53,75,127],"are":[55,107],"stochastic,":[56],"such":[57],"as":[58,74,78],"the":[59,135],"tactical":[60],"air":[61],"combat":[62],"simulation":[63],"BRAWLER.":[64],"Distributional":[65],"information":[66],"lost":[68],"when":[69],"transferring":[70],"output":[71],"BRAWLER":[73,100],"for":[76,125,140],"point":[79,123],"estimates.":[80],"These":[81],"problems":[82],"cannot":[83],"be":[84],"solved":[85],"standard":[87],"comparison":[88],"techniques":[89,116,139],"(e.g.":[90],"Tukey's,":[91],"Fisher's)":[92],"because":[93],"they":[94],"assume":[95],"normally":[96],"distributed":[97],"data":[98,101,130],"(which":[99],"does":[102],"not":[103],"satisfy)":[104],"both":[106],"\u201coverwhelmed\u201d":[108],"large":[110],"number":[111],"comparisons.":[113],"Combining":[114],"bootstrapping":[115],"with":[117],"clustering":[118],"methods,":[119],"AF/A9":[120],"has":[121],"created":[122],"estimates":[124],"data,":[128],"maintaining":[129],"integrity.":[131],"This":[132],"presentation":[133],"describes":[134],"initial":[136],"using":[141],"this":[142],"process":[143],"in":[144],"other":[145],"stochastic-to-deterministic":[146],"model":[147],"integrations.":[148]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}