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首页> 外文期刊>International journal of computing science and mathematics >An improved flower pollination algorithm for solving nonlinear system of equations
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An improved flower pollination algorithm for solving nonlinear system of equations

机译：一种改进的方程式非线性系统的改进的花授粉算法

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摘要

It is difficult to solve a system of nonlinear equations, especially for higher-order nonlinear equations when we do not have an efficient and reliable algorithm, even though much work has been done in this area. Newton's method and its improved form are widely used at present, but their convergence and performance characteristics can be highly sensitive to the initial guess of the solution, and the methods fail if the initial guess of the solution is inopportune. It is difficult to select a good initial guess for most systems of nonlinear equations. For this reason, it is necessary to find an efficient algorithm for systems of nonlinear equations. Metaheuristic optimisation algorithms have been proposed by many researchers to solve systems of nonlinear equations. The flower pollination algorithm (FPA) is a novel metaheuristic optimisation algorithm with quick convergence, but its population diversity and convergence precision can be limited in some applications. To enhance its exploitation and exploration abilities, in this paper, an elite opposition-based flower pollination algorithm (EFPA) has been applied for solving systems of nonlinear equations. The results show that the proposed algorithm is robust, has high convergence rate and precision, and can give satisfactory solutions of nonlinear equations.
机译：当我们没有高效可靠的算法时，难以解决非线性方程系统，特别是对于高阶非线性方程，即使在该区域完成了很多工作。目前牛顿的方法及其改进的形式被广泛使用，但它们的收敛性和性能特征可以对解决方案的初始猜测非常敏感，并且如果解决方案的初始猜测，则方法失败。对于大多数非线性方程系统，难以选择良好的初步猜测。因此，有必要找到非线性方程系统的有效算法。许多研究人员提出了若干研究人员来解决非线性方程的系统。花授粉算法（FPA）是一种新型融合综合优化算法，但其群体多样性和收敛精度可限制在某些应用中。为了提高其开发和勘探能力，本文已施加了一种精英对抗的花授粉算法（EFPA），用于求解非线性方程的系统。结果表明，该算法具有稳健，具有高收敛速度和精度，并可提供非线性方程的令人满意的解。

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