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Research on ill-conditioned problem in grey prediction control model

机译:灰色预测控制模型中的病态问题研究

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A new simple and effective method for solving ill-conditioned GM(1,1) model in grey prediction controller is proposed. This method is based on multiple transformation to original series and center parallel moving transformation to AGO series. By choosing coefficients M and /spl rho/, the condition number of coefficient matrix can be controlled. This method not only improves the prediction accuracy of the original grey model, but also reduces ill-conditions for GM (1,1) model. Finally we use an application example for our case study to test the efficiency and accuracy of the proposed method.
机译:提出了一种在灰色预测控制器中解决不良动态的GM(1,1)模型的一种新的简单有效方法。此方法基于多个转换为原始系列和中心并行移动变换,致术语。通过选择系数m和/ spl rho /,可以控制系数矩阵的条件数量。该方法不仅提高了原始灰色模型的预测准确性,而且还减少了GM(1,1)模型的不良条件。最后,我们使用应用程序示例进行案例研究以测试所提出的方法的效率和准确性。

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