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MODELING OF FLEXIBLE STRUCTURES BY MEANS OF LEAST SQUARE SUPPORT VECTOR MACHINE

机译:柔性结构借助于最小二乘支持向量机建模

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This paper investigates modeling of flexible structures by means of the least squares support vector machine (LS-SVM) algorithm. Modeling is the first step to obtain a suitable model-based controller for any given system. Accurate modeling of a flexible structure based on experimental data using LS-SVM algorithm requires less knowledge about the physical system. Least squares support vector machine algorithm can achieve global and unique solution when compared with other soft computing algorithms. Also, LS-SVM algorithm requires less training time. In this paper, the successful use of support vector machine algorithm to model the flexible cantilever is demonstrated. The acquired model is able to provide accurate prediction of the system output under different operating conditions. Experimental results demonstrate the efficiency and high precision of the proposed approach.
机译:本文通过最小二乘支持向量机(LS-SVM)算法来研究灵活结构的建模。建模是获得适用于任何给定系统的合适模型的控制器的第一步。基于使用LS-SVM算法的实验数据的灵活结构的精确建模需要对物理系统的知识较少。与其他软计算算法相比,最小二乘支持向量机算法可以实现全局和独特的解决方案。此外,LS-SVM算法需要较少的培训时间。在本文中,对支持向量机算法进行了模拟柔性悬臂的成功使用。所获取的模型能够在不同的操作条件下提供对系统输出的精确预测。实验结果表明了所提出的方法的效率和高精度。

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