{"title":"自适应高斯搜索:一种新颖的非线性最小化技术[总统奖程序]","authors":"Koichi OSHIO","doi":"10.2463/jjmrm.2022-1775","DOIUrl":null,"url":null,"abstract":"A novel minimization technique was developed. The proposed method is based on a Gaussian random search in the parameter space and it can handle a wide range of problems, including bi-exponential curve fitting, in a reasonable time. It uses only function values, and does not require gradients.","PeriodicalId":471579,"journal":{"name":"Nihon Jiki Kyōmei Igakkai zasshi","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Gaussian Search : A Novel Non-linear Minimization Technique [Presidential Award Proceedings]\",\"authors\":\"Koichi OSHIO\",\"doi\":\"10.2463/jjmrm.2022-1775\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A novel minimization technique was developed. The proposed method is based on a Gaussian random search in the parameter space and it can handle a wide range of problems, including bi-exponential curve fitting, in a reasonable time. It uses only function values, and does not require gradients.\",\"PeriodicalId\":471579,\"journal\":{\"name\":\"Nihon Jiki Kyōmei Igakkai zasshi\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nihon Jiki Kyōmei Igakkai zasshi\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2463/jjmrm.2022-1775\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nihon Jiki Kyōmei Igakkai zasshi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2463/jjmrm.2022-1775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Gaussian Search : A Novel Non-linear Minimization Technique [Presidential Award Proceedings]
A novel minimization technique was developed. The proposed method is based on a Gaussian random search in the parameter space and it can handle a wide range of problems, including bi-exponential curve fitting, in a reasonable time. It uses only function values, and does not require gradients.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
