{"title":"利用模糊SPRT改进序贯抽样方案","authors":"R. Afshari, B. S. Gildeh","doi":"10.1109/CFIS.2017.8003668","DOIUrl":null,"url":null,"abstract":"In this paper, a modified attribute sequential sampling plan (SSP) for fuzzy hypotheses testing is proposed with crisp data. Unlike existing fuzzy SSP, the modified plan partitions continue sampling region into three parts, and decides the submitted lot based on which part the plotted point is appeared according to its corresponding degree. For such a plan, the authors construct particular table of fuzzy acceptance and rejection numbers as well as plotted fuzzy acceptance and rejection lines for different values of ambiguity. In order to be fully informed, a practical example is also discussed. The obtained result shows that the modified plan is well-defined since it converts to a classical plan as the parameters are crisp.","PeriodicalId":398605,"journal":{"name":"2017 5th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Modified sequential sampling plan using fuzzy SPRT\",\"authors\":\"R. Afshari, B. S. Gildeh\",\"doi\":\"10.1109/CFIS.2017.8003668\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a modified attribute sequential sampling plan (SSP) for fuzzy hypotheses testing is proposed with crisp data. Unlike existing fuzzy SSP, the modified plan partitions continue sampling region into three parts, and decides the submitted lot based on which part the plotted point is appeared according to its corresponding degree. For such a plan, the authors construct particular table of fuzzy acceptance and rejection numbers as well as plotted fuzzy acceptance and rejection lines for different values of ambiguity. In order to be fully informed, a practical example is also discussed. The obtained result shows that the modified plan is well-defined since it converts to a classical plan as the parameters are crisp.\",\"PeriodicalId\":398605,\"journal\":{\"name\":\"2017 5th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 5th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CFIS.2017.8003668\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CFIS.2017.8003668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modified sequential sampling plan using fuzzy SPRT
In this paper, a modified attribute sequential sampling plan (SSP) for fuzzy hypotheses testing is proposed with crisp data. Unlike existing fuzzy SSP, the modified plan partitions continue sampling region into three parts, and decides the submitted lot based on which part the plotted point is appeared according to its corresponding degree. For such a plan, the authors construct particular table of fuzzy acceptance and rejection numbers as well as plotted fuzzy acceptance and rejection lines for different values of ambiguity. In order to be fully informed, a practical example is also discussed. The obtained result shows that the modified plan is well-defined since it converts to a classical plan as the parameters are crisp.