{"title":"用蒙特卡罗方法求解偏微分方程的混合计算机解","authors":"W. Little","doi":"10.1145/1464291.1464312","DOIUrl":null,"url":null,"abstract":"In addition to finite-difference methods, Monte Carlo methods also are known for solving certain partial differential equations. When implemented on a digital computer, however, the Monte Carlo methods have generally proven to be very inefficient. In 1960, a study carried out at the University of Michigan described analog computer techniques for mechanizing Monte Carlo methods. From the Michigan study it became evident that a fast analog computer together with a small digital computer and a modest interface could obtain Monte Carlo solutions at rates competitive with standard finite-difference methods.","PeriodicalId":297471,"journal":{"name":"AFIPS '66 (Fall)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1899-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Hybrid computer solutions of partial differential equations by Monte Carlo methods\",\"authors\":\"W. Little\",\"doi\":\"10.1145/1464291.1464312\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In addition to finite-difference methods, Monte Carlo methods also are known for solving certain partial differential equations. When implemented on a digital computer, however, the Monte Carlo methods have generally proven to be very inefficient. In 1960, a study carried out at the University of Michigan described analog computer techniques for mechanizing Monte Carlo methods. From the Michigan study it became evident that a fast analog computer together with a small digital computer and a modest interface could obtain Monte Carlo solutions at rates competitive with standard finite-difference methods.\",\"PeriodicalId\":297471,\"journal\":{\"name\":\"AFIPS '66 (Fall)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1899-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AFIPS '66 (Fall)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1464291.1464312\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AFIPS '66 (Fall)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1464291.1464312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid computer solutions of partial differential equations by Monte Carlo methods
In addition to finite-difference methods, Monte Carlo methods also are known for solving certain partial differential equations. When implemented on a digital computer, however, the Monte Carlo methods have generally proven to be very inefficient. In 1960, a study carried out at the University of Michigan described analog computer techniques for mechanizing Monte Carlo methods. From the Michigan study it became evident that a fast analog computer together with a small digital computer and a modest interface could obtain Monte Carlo solutions at rates competitive with standard finite-difference methods.