Open AccessModified Monte Carlo method for integral
Author(s) -
Said Iskandar
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1462/1/012061
Subject(s) - monte carlo method , monte carlo integration , quasi monte carlo method , hybrid monte carlo , monte carlo molecular modeling , monte carlo method in statistical physics , dynamic monte carlo method , mathematics , function (biology) , numerical integration , quantum monte carlo , mathematical optimization , computer science , statistical physics , markov chain monte carlo , mathematical analysis , statistics , physics , evolutionary biology , biology
The integral value of a function will be determined by the result of the function of the integral function. In fact many integral functions that are difficult to solve sometimes cannot be solved by exact sciences. There are several ways such as by changing its function toThe approach to the Monte Carlo method uses the principle of generating random numbers to test a function. The use of randoms is very closely related to the value of the error obtained. This study aims to minimize the error value of integration by using the Monte Carlo method. The initial integration of the Monte Carlo method with 10000 random points has a fairly large average error value of 0.078, so that the follow-up is done using pias in the Monte Carlo integration.