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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >Modeling of fractional order chaotic systems using artificial bee colony optimization and ant colony optimization
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Modeling of fractional order chaotic systems using artificial bee colony optimization and ant colony optimization

机译:使用人工蜂殖民地优化和蚁群优化建模分数秩序混沌系统

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摘要

In this paper, a modified Artificial Bee Colony algorithm is proposed. Then estimation of the parameters of fractional order chaotic systems is performed using the proposed Artificial Bee Colony algorithm and Ant Colony algorithm. For the purpose of modeling, four fractional order chaotic systems viz. Financial System, Chen System, Lorenz's system and 3 Cell Net system have been considered. Each chaotic system is defined by a set of fractional-order differential equations. These equations comprise of several variables - model parameters, derivative orders, and initial conditions. For the system's entire state and future values to be known, the values of all the parameters have to be estimated to a reasonable degree of accuracy. It is a general practice to use modern evolutionary algorithms to solve such problems. Simulations on both nature inspired optimization algorithms are performed and estimated values of parameters determined. Comparisons with existing scheme of Artificial Bee Colony based parameter estimation are also performed. Observations reveal that the results of the modified ABC algorithm outperform those of other techniques for all the four cases.
机译:本文提出了一种改进的人工蜂菌落算法。然后使用所提出的人造蜂菌落算法和蚁群算法来执行分数阶混沌系统参数的估计。为建模目的,四个分数秩序混沌系统ZIZ。已经考虑了金融系统,陈系统,洛伦茨系统和3个细胞网系统。每个混沌系统由一组分数级微分方程定义。这些方程包括多个变量 - 模型参数,衍生订单和初始条件。对于系统的整个状态和未来值,必须估计所有参数的值,以合理的准确度。使用现代进化算法来解决这些问题是一般的做法。对自然启发优化算法进行了模拟,并确定了参数的估计值。还执行了利用现有的基于人造群基于人工群的参数估计方案的比较。观察结果表明,修改的ABC算法的结果优于所有四种情况的其他技术的结果。

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