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An Approximate Solution for a Simple Pendulum beyond the Small Angles Regimes Using Hybrid Artificial Neural Network and Particle Swarm Optimization Algorithm

机译:一种超出使用混合人工神经网络和粒子群优化算法超出小角度制度之外的简单摆的近似解

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Simple pendulum is the most popular example in mechanics. Study on the physics of simple pendulum is a key to understanding the nonlinear dynamics of many other systems. However, there is an exact analytical solution for this problem, but its exact solution is in the form of the Jacobi elliptic integral which it is hard for using in simple engineering manipulations. Hence, determining an accurate simple approximate solution is helpful. This study presents a new method by using hybrid neural networks and particle swarm optimization algorithm, in order to find a simple approximate solution for motion of a nonlinear pendulum beyond the small angles regime. The approximate solution is simple and powerful to converge to the exact solution. The results of the approximate solution are compared with exact solution and linear solution, using tables and graphs. Furthermore, the present method is expandable to solve complex pendulums.
机译:简单的摆锤是力学中最受欢迎的例子。关于简单摆锤的物理学的研究是了解许多其他系统的非线性动态的关键。然而,有一个精确的分析解决方案对于这个问题,但其精确的解决方案是雅各比椭圆形的形式,这是难以在简单的工程操纵中使用的。因此,确定准确的简单近似解决方案是有帮助的。本研究通过使用混合神经网络和粒子群优化算法提出了一种新方法,以便找到超出小角度范围内的非线性摆的运动的简单近似解。近似解决方案简单且强大,可以收敛到确切的解决方案。使用表格和图表将近似解的结果与精确的溶液和线性解决方案进行比较。此外,本方法可扩展以求解复杂的摆锤。

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