{"title":"基于网格自适应直接搜索优化的Dirichlet边值问题数值解","authors":"Muhammad Jalil Ahmad, K. Günel","doi":"10.52460/issc.2021.030","DOIUrl":null,"url":null,"abstract":"This study gives a different numerical approach for solving second order differential equation with a Dirichlet boundary condition. Mesh Adaptive Direct Search (MADS) algorithm is adopted to train the feed forward neural network used in this approach. As MADS is a derivative-free optimization algorithm, it helps us to reduce the time-consuming workload in the training stage. The results obtained from this approach are also compared with Generalized Pattern Search (GPS) algorithm.","PeriodicalId":136262,"journal":{"name":"5th International Students Science Congress","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Numerical Solution of Dirichlet Boundary Value Problems using Mesh Adaptive Direct Search Optimization\",\"authors\":\"Muhammad Jalil Ahmad, K. Günel\",\"doi\":\"10.52460/issc.2021.030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study gives a different numerical approach for solving second order differential equation with a Dirichlet boundary condition. Mesh Adaptive Direct Search (MADS) algorithm is adopted to train the feed forward neural network used in this approach. As MADS is a derivative-free optimization algorithm, it helps us to reduce the time-consuming workload in the training stage. The results obtained from this approach are also compared with Generalized Pattern Search (GPS) algorithm.\",\"PeriodicalId\":136262,\"journal\":{\"name\":\"5th International Students Science Congress\",\"volume\":\"125 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th International Students Science Congress\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52460/issc.2021.030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th International Students Science Congress","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52460/issc.2021.030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Numerical Solution of Dirichlet Boundary Value Problems using Mesh Adaptive Direct Search Optimization
This study gives a different numerical approach for solving second order differential equation with a Dirichlet boundary condition. Mesh Adaptive Direct Search (MADS) algorithm is adopted to train the feed forward neural network used in this approach. As MADS is a derivative-free optimization algorithm, it helps us to reduce the time-consuming workload in the training stage. The results obtained from this approach are also compared with Generalized Pattern Search (GPS) algorithm.
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