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Numerical Solution of Linear Regression Based on Z-Numbers by Improved Neural Network

机译:基于Z值的线性回归的改进神经网络数值解。

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In this article, the researcher at first focuses on introducing a linear regression based on the Z-number. In this regression, observations are real, but the coefficients and results of observations are unknown and in the form of Z-rating. Therefore, to estimate this type of regression, we have three distinct ways depending on different conditions dominating the problem. The three methods are a combination of artificial neural networks and fuzzy generalized improvements of the technique. Moreover the method of calculating the weights of the Z-number neural network has been mentioned and the stability of neural network weights is considered. In some examples, the answer is estimated compared with the original answer.
机译:在本文中,研究人员首先着重介绍基于Z数的线性回归。在这种回归中,观测值是真实的,但观测值的系数和结果未知,并且采用Z等级的形式。因此,要估计这种类型的回归,我们可以采用三种不同的方法,这取决于控制问题的不同条件。这三种方法是人工神经网络和该技术的模糊广义改进的结合。此外,还提到了计算Z值神经网络权重的方法,并考虑了神经网络权重的稳定性。在一些示例中,将答案与原始答案进行比较。

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