Jasveer Singh, L. Kumaraswamidhas, Neha Bura, K. Kaushik, N. Sharma
{"title":"一种简化的蒙特卡罗法不确定性估计软件","authors":"Jasveer Singh, L. Kumaraswamidhas, Neha Bura, K. Kaushik, N. Sharma","doi":"10.1166/ASEM.2020.2667","DOIUrl":null,"url":null,"abstract":"The current paper discusses about the application of Monte Carlo method for the evaluation of measurement uncertainty using in-house developed program on C++ platform. The Monte Carlo method can be carried out by fixed trials as well as adaptive trials using this program. The program\n provides the four parameters viz. estimate of measurand, standard uncertainty in the form of standard deviation and end points of coverage interval as an output.","PeriodicalId":7213,"journal":{"name":"Advanced Science, Engineering and Medicine","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Simplified Software for Uncertainty Estimation Using Monte Carlo Method\",\"authors\":\"Jasveer Singh, L. Kumaraswamidhas, Neha Bura, K. Kaushik, N. Sharma\",\"doi\":\"10.1166/ASEM.2020.2667\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The current paper discusses about the application of Monte Carlo method for the evaluation of measurement uncertainty using in-house developed program on C++ platform. The Monte Carlo method can be carried out by fixed trials as well as adaptive trials using this program. The program\\n provides the four parameters viz. estimate of measurand, standard uncertainty in the form of standard deviation and end points of coverage interval as an output.\",\"PeriodicalId\":7213,\"journal\":{\"name\":\"Advanced Science, Engineering and Medicine\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Science, Engineering and Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1166/ASEM.2020.2667\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science, Engineering and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1166/ASEM.2020.2667","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Simplified Software for Uncertainty Estimation Using Monte Carlo Method
The current paper discusses about the application of Monte Carlo method for the evaluation of measurement uncertainty using in-house developed program on C++ platform. The Monte Carlo method can be carried out by fixed trials as well as adaptive trials using this program. The program
provides the four parameters viz. estimate of measurand, standard uncertainty in the form of standard deviation and end points of coverage interval as an output.