{"title":"方差分析在不同钇钡铜氧化物超导转变温度建模中的应用","authors":"A. Maksuwan, Arpapong Changjan, P. Pramuanl","doi":"10.55766/sujst-2023-05-e02267","DOIUrl":null,"url":null,"abstract":"Extensive research has been conducted on a modeling approach that contributes to predicting the critical temperature of Yttrium barium copper oxide (YBCO) materials. Statistical significance of differences in modeling approaches requires studies that can reliably distinguish between systematic approach effects and errors resulting from modeling approach variation. In this work, we introduce analysis of variance (ANOVA) to assess the statistical significance of differences in modeling approach variation. Comparisons of obtained results with YBCO modeling approach variation data of support vector machine (SVM) and linear regression with natural logarithm transformation (LRNLT) were presented.","PeriodicalId":43478,"journal":{"name":"Suranaree Journal of Science and Technology","volume":"194 1","pages":""},"PeriodicalIF":0.2000,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"THE APPLICATION OF ANALYSIS OF VARIANCE TO DIFFERENT YTTRIUM BARIUM COPPER OXIDE SUPERCONDUCTING TRANSITION TEMPERATURE MODELING\",\"authors\":\"A. Maksuwan, Arpapong Changjan, P. Pramuanl\",\"doi\":\"10.55766/sujst-2023-05-e02267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Extensive research has been conducted on a modeling approach that contributes to predicting the critical temperature of Yttrium barium copper oxide (YBCO) materials. Statistical significance of differences in modeling approaches requires studies that can reliably distinguish between systematic approach effects and errors resulting from modeling approach variation. In this work, we introduce analysis of variance (ANOVA) to assess the statistical significance of differences in modeling approach variation. Comparisons of obtained results with YBCO modeling approach variation data of support vector machine (SVM) and linear regression with natural logarithm transformation (LRNLT) were presented.\",\"PeriodicalId\":43478,\"journal\":{\"name\":\"Suranaree Journal of Science and Technology\",\"volume\":\"194 1\",\"pages\":\"\"},\"PeriodicalIF\":0.2000,\"publicationDate\":\"2023-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Suranaree Journal of Science and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.55766/sujst-2023-05-e02267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Suranaree Journal of Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.55766/sujst-2023-05-e02267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
THE APPLICATION OF ANALYSIS OF VARIANCE TO DIFFERENT YTTRIUM BARIUM COPPER OXIDE SUPERCONDUCTING TRANSITION TEMPERATURE MODELING
Extensive research has been conducted on a modeling approach that contributes to predicting the critical temperature of Yttrium barium copper oxide (YBCO) materials. Statistical significance of differences in modeling approaches requires studies that can reliably distinguish between systematic approach effects and errors resulting from modeling approach variation. In this work, we introduce analysis of variance (ANOVA) to assess the statistical significance of differences in modeling approach variation. Comparisons of obtained results with YBCO modeling approach variation data of support vector machine (SVM) and linear regression with natural logarithm transformation (LRNLT) were presented.