The Task of Structural Identification the Interval Models of Static Objects with Multiple Parameters

M. Dyvak, A. Pukas, V. Manzhula, O. Papa, Amantius Akimjak, Bogdan Maslyiak
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Abstract

In the paper formulated the static objects’ interval models’ structure identification problem as repeatedly searching of interval systems of nonlinear algebraic equations (ISNAE) solutions, in the optimization problem’s form with nonlinear goal function and nonlinear constraints. For the first time, a method of structure identification of static objects’ characteristics interval models by the analysis of interval data was substantiated and development. The method is based on the use of the artificial bee colony algorithm. The justification of the advantage of the proposed method in comparison with known ones based on genetic algorithms is given.
多参数静态目标区间模型的结构识别任务
本文将静态目标区间模型结构辨识问题以非线性目标函数和非线性约束的优化问题形式表述为重复搜索非线性代数方程组(ISNAE)解。首次提出了一种基于区间数据分析的静态目标特征区间模型结构识别方法。该方法基于人工蜂群算法的使用。通过与现有遗传算法的比较,证明了该方法的优越性。
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