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A family of higher order multi-point iterative methods based on power mean for solving nonlinear equations

机译:一类基于幂均值的高阶多点迭代方法,用于求解非线性方程

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摘要

In this paper, we have presented a family of two-point fourth order, three-point sixth order and four-point twelfth order iterative methods without memory based on power mean using weight function. The family of fourth order methods is optimal in the sense of Kung-Traub hypothesis. In terms of computational point of view, our methods require three evaluations (one function and two first derivatives) to get fourth order, four evaluations (two functions and two derivatives) to get sixth order and five evaluations (three functions and two derivatives) to get twelfth order. Hence, these methods have high efficiency indices 1.587, 1.565 and 1.644 respectively. Few known results can be regarded as particular cases of our family of methods. Some numerical examples are tested to know the efficiencies of the methods which verify the theoretical results.
机译:在本文中,我们基于权重均值的幂均值,提出了一种无需记忆的两点四阶,三点六阶和四点十二阶迭代方法。在Kung-Traub假设的意义上,四阶方法族是最优的。从计算的角度来看,我们的方法需要三个评估(一个函数和两个一阶导数)来获得四阶,四个评估(两个函数和两个导数)来获得六阶和五个评估(三个函数和两个导数)以得到得到第十二个订单。因此,这些方法分别具有高效率指数1.587、1.565和1.644。很少有已知结果可被视为我们方法系列的特例。测试了一些数值示例,以了解验证理论结果的方法的效率。

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