{"title":"Embedded Statistical Analysis and Selection Procedures in Air Traffic Simulations","authors":"Kirk C. Benson, A. Pritchett, D. Goldsman","doi":"10.2514/ATCQ.19.4.269","DOIUrl":null,"url":null,"abstract":"Statistical analysis and adaptive sampling techniques can be embedded within existing air traffic simulations to provide several benefits. First, embedded statistical calculations can eliminate the need for extensive storage and post hoc processing of simulated outputs. Second, adaptive sampling can identify the number of observations required for rigorous statistical comparison, often dramatically reducing the number and duration of simulation runs from those predicted a priori by standard statistical techniques, which tend to be quite conservative. Third, these methods facilitate efficient distribution of simulator runs over a network of workstations without requiring parallelization of the simulation software.This paper describes three central components required for these benefits: (1) embedded statistical calculations; (2) adaptive statistical selection techniques; and (3) the server-client structure for a network of workstations in which individual workstations gather and report interim statistics a...","PeriodicalId":221205,"journal":{"name":"Air traffic control quarterly","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Air traffic control quarterly","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/ATCQ.19.4.269","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Statistical analysis and adaptive sampling techniques can be embedded within existing air traffic simulations to provide several benefits. First, embedded statistical calculations can eliminate the need for extensive storage and post hoc processing of simulated outputs. Second, adaptive sampling can identify the number of observations required for rigorous statistical comparison, often dramatically reducing the number and duration of simulation runs from those predicted a priori by standard statistical techniques, which tend to be quite conservative. Third, these methods facilitate efficient distribution of simulator runs over a network of workstations without requiring parallelization of the simulation software.This paper describes three central components required for these benefits: (1) embedded statistical calculations; (2) adaptive statistical selection techniques; and (3) the server-client structure for a network of workstations in which individual workstations gather and report interim statistics a...