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

被引：1
|
作者：
Yekrangi, Alireza [2 ]
Ghalambaz, Mehdi [3 ]
Noghrehabadi, Aminreza [1 ]
Beni, Yaghoub Tadi [4 ]
Abadyan, Mohamadreza [2 ]
Abadi, Molood Noghreh [5 ]
Abadi, Mehdi Noghreh [6 ]
机构：
[1] Islamic Azad Univ, Ahvaz Branch, Dept Mech Engn, Ahvaz, Iran
[2] Islamic Azad Univ, Ramsar Branch, Mech Engn Grp, Ramsar, Iran
[3] Islamic Azad Univ, Dezful Brach, Dept Engn Mech, Dezful, Iran
[4] Univ Shahrekord, Fac Engn, Shahrekord, Iran
[5] Islamic Azad Univ, Dezful Branch, Dept Comp Engn, Dezful, Iran
[6] Islamic Azad Univ, Khouzestan Sci & Res Branch, Ahvaz, Iran
来源：
11TH INTERNATIONAL CONFERENCE ON THE MECHANICAL BEHAVIOR OF MATERIALS (ICM11) | 2011年 / 10卷
关键词：
Simple pendulum; Differential equation; Neural networks; Particle Swarm Optimization (PSO);
D O I：
10.1016/j.proeng.2011.04.611
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
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. (C) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of ICM11
引用
收藏
页码：3734 / 3740
页数：7
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