Comparison on Trapezoidal and Simpson’s Rule for Unequal Data Space

M. N. Dhali, Mohammad Farhad Bulbul, U. Sadiya
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引用次数: 3

Abstract

Numerical integration compromises a broad family of algorithm for calculating the numerical value of a definite integral. Since some of the integration cannot be solved analytically, numerical integration is the most popular way to obtain the solution. Many different methods are applied and used in an attempt to solve numerical integration for unequal data space. Trapezoidal and Simpson’s rule are widely used to solve numerical integration problems. Our paper mainly concentrates on identifying the method which provides more accurate result. In order to accomplish the exactness we use some numerical examples and find their solutions. Then we compare them with the analytical result and calculate their corresponding error. The minimum error represents the best method. The numerical solutions are in good agreement with the exact result and get a higher accuracy in the solutions.
不等数据空间的梯形规则与辛普森规则的比较
数值积分包含了一系列计算定积分数值的算法。由于有些积分不能解析求解,所以数值积分是最常用的求解方法。许多不同的方法被应用于求解不等数据空间的数值积分。梯形规则和辛普森规则被广泛用于求解数值积分问题。本文主要研究的是如何确定一种能提供更准确结果的方法。为了达到精确的目的,我们使用了一些数值例子并求出了它们的解。然后与分析结果进行了比较,并计算了相应的误差。误差最小代表最佳方法。数值解与实际结果吻合较好,解的精度较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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