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A Novel Simplified Foraging Optimization Algorithm for Parameter Identification of Nonlinear System Model

机译:非线性系统模型参数辨识的新型简化寻觅优化算法

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A simplified E. Coli foraging optimization algorithm based on the chemotactic behaviour of E. Col is presented in this paper in order to solve the parameter estimation of nonlinear system model (NSM). The simplified E. Coli algorithm consists of a tumbling operator and a swimming operator and at the same time the optimal position of individual E. Coli and the location of all E. Coli swarm are adopted to update the locations of swarm. The effectiveness of the proposed simplified E. Coli foraging optimization algorithm is demonstrated by simulation experiments on the parameter estimation of the NSM for heavy oil thermal cracking. The results indicate that the simplified E. Coli model is valid and provides an attractive method for the estimation of parameters of NSM.
机译:为了解决非线性系统模型(NSM)的参数估计问题,提出了一种基于E. Col趋化行为的简化E. Coli觅食优化算法。简化的大肠杆菌算法由翻滚算子和游泳算子组成,同时采用单个大肠杆菌的最佳位置和所有大肠杆菌群的位置来更新群的位置。通过对重油热裂化NSM参数估计的仿真实验,证明了所提出的简化的大肠杆菌觅食优化算法的有效性。结果表明,简化的大肠杆菌模型是有效的,为NSM参数的估计提供了一种有吸引力的方法。

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