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A new fuzzy regression model based on interval-valued fuzzy neural network and its applications to management

机译:基于区间值模糊神经网络的新模糊回归模型及其在管理中的应用

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In this paper, a novel hybrid method based on interval-valued fuzzy neural network for approximate of interval-valued fuzzy regression models, is presented. The work of this paper is an expansion of the research of real fuzzy regression models. In this paper interval-valued fuzzy neural network (IVFNN) can be trained with crisp and interval-valued fuzzy data. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples and compare this method with existing methods.
机译:提出了一种基于区间值模糊神经网络的区间值模糊回归模型的近似混合方法。本文的工作是对实际模糊回归模型的研究的扩展。在本文中,区间值模糊神经网络(IVFNN)可以使用清晰的区间值模糊数据进行训练。在这里,神经网络被认为是称为神经计算或软计算的大领域的一部分。此外,为了找到近似参数,提出了一种基于模糊神经网络代价函数的简单算法。最后,我们通过一些数值示例来说明我们的方法,并将此方法与现有方法进行比较。

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