Use of a sine cosine algorithm combined with Simpson method for numerical integration

M. Abdel-Baset, Yongquan Zhou, Ibrahim M. Hezam
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引用次数: 6

Abstract

The sine cosine algorithm (SCA) is one of the most recent nature-inspired meta-heuristic optimisation algorithm, which the mathematical model based on sine and cosine functions. SCA has validated excellent performance in solving continuous problems and engineering optimisation problems. In this paper, we propose a new algorithm that encompasses the features of sine cosine algorithm and Simpson method (SCA-SM). The proposed procedure consists of two phases: in the first phase, the of sine cosine algorithm are used to find the optimal segmentation points on the integral interval of an integrand. In the second phase, the approximate integral value of the integrand is then calculated by a Simpson method. Numerical simulation results show that the algorithm offers an effective way to calculate numerical value of definite integrals, and it has a high convergence rate, high accuracy and robustness.
利用正弦余弦算法结合辛普森法进行数值积分
正弦余弦算法(SCA)是一种基于正弦和余弦函数的数学模型,基于自然启发的元启发式优化算法。SCA在解决连续问题和工程优化问题方面表现出色。本文提出了一种集正弦余弦算法和辛普森方法(SCA-SM)的特点于一体的新算法。该算法分为两个阶段:第一阶段,利用正弦余弦算法在被积函数的积分区间上寻找最优分割点;在第二阶段,用辛普森法计算被积函数的近似积分值。数值仿真结果表明,该算法为计算定积分数值提供了一种有效的方法,具有较高的收敛速度、精度和鲁棒性。
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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