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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Adaptive infinite impulse response system identification using opposition based hybrid coral reefs optimization algorithm
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Adaptive infinite impulse response system identification using opposition based hybrid coral reefs optimization algorithm

机译：基于混合珊瑚礁的自适应无限脉冲响应系统识别优化算法

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摘要

An efficient global adaptive algorithm is required to determine the parameters of infinite impulse response (IIR) filter owing to the error cost surface of adaptive IIR system identification problem being generally nonlinear and non-differentiable. In this paper, a new bio-inspired algorithm, called opposition based hybrid coral reefs optimization algorithm (OHCRO) is applied for the IIR system identification problem. Coral reefs optimization algorithm (CRO) is a novel global algorithm, which mimics the behaviors of corals' reproduction and coral reef formation. OHCRO is a modified version of CRO, on the one hand utilizing opposition based learning to accelerate global convergence, on the other hand cooperating with rotational direction method to enhance the local search capability. In addition, the Laplace broadcast spawning and power mutation brooding operator are used to maintain the diversity. The simulation studies have been performed for the performance comparison of genetic algorithm, particle swarm optimization and its variants, differential evolution and its variants and the proposed OHCRO for well-known benchmark examples with same order and reduced order filters. Simulation results and comparative studies justify the efficacy of the OHCRO based system identification approach in terms of convergence speed, identified coefficients and fitness values. In conclusion, OHCRO is a promising method for adaptive IIR system identification.
机译：需要一种有效的全局自适应算法来确定由于自适应IIR系统识别问题的误差成本表面通常是非线性和不可微分的误差成本表面的无限脉冲响应（IIR）滤波器的参数。本文应用了一种新的生物启发算法，称为对立的混合珊瑚礁优化算法（OHCHCRO）被应用于IIR系统识别问题。珊瑚礁优化算法（CRO）是一种新型全局算法，模仿珊瑚速和珊瑚礁形成的行为。 Ohcro是CRO的修改版本，一方面利用基于反对派的学习来加速全球收敛，另一方面与旋转方向法协作，以提高本地搜索能力。此外，Laplace广播产卵和功率突变育雏术供应商用于维持多样性。已经对遗传算法，粒子群优化及其变体，差分演化及其变体的性能比较进行了仿真研究，以及具有相同订单和减少订单过滤器的众所周知基准示例所提出的基准。仿真结果与比较研究证明了基于基于系统识别方法的效果，在收敛速度，识别的系数和健身值方面。总之,HCHRO是适应性IIR系统识别的有希望的方法。

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