{"title":"用模糊逻辑近似求解线性方程组的准确率","authors":"Awni M. Abu-Saman","doi":"10.28919/jmcs/6867","DOIUrl":null,"url":null,"abstract":"This paper proposes a numerical procedure for determining rate of accuracy of the numerical method used for solving a system of linear equations Ax=b. The idea of the method depends on the fuzzy value of the condition number and singularity rate instead of the crisp values. The procedure will be implemented on the mathematical code MATLAB and it’s Simulink features. Finally the applicability and efficiency of the procedure is illustrated by a numerical example.","PeriodicalId":36607,"journal":{"name":"Journal of Mathematical and Computational Science","volume":"16 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using fuzzy logic to approximate the accuracy rate in solving a system of linear equations\",\"authors\":\"Awni M. Abu-Saman\",\"doi\":\"10.28919/jmcs/6867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a numerical procedure for determining rate of accuracy of the numerical method used for solving a system of linear equations Ax=b. The idea of the method depends on the fuzzy value of the condition number and singularity rate instead of the crisp values. The procedure will be implemented on the mathematical code MATLAB and it’s Simulink features. Finally the applicability and efficiency of the procedure is illustrated by a numerical example.\",\"PeriodicalId\":36607,\"journal\":{\"name\":\"Journal of Mathematical and Computational Science\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mathematical and Computational Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.28919/jmcs/6867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical and Computational Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.28919/jmcs/6867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Mathematics","Score":null,"Total":0}
Using fuzzy logic to approximate the accuracy rate in solving a system of linear equations
This paper proposes a numerical procedure for determining rate of accuracy of the numerical method used for solving a system of linear equations Ax=b. The idea of the method depends on the fuzzy value of the condition number and singularity rate instead of the crisp values. The procedure will be implemented on the mathematical code MATLAB and it’s Simulink features. Finally the applicability and efficiency of the procedure is illustrated by a numerical example.