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Modeling Data under Non-additive Measure-a Theoretical Frame and Some Applications

机译:非加性度量下的建模数据 - 理论框架和一些应用

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In this paper, we study how to estimate the nonlinear multi-regression model based upon fuzzy integral (either Choquet integral or (S)ipo(s) integral), and then propose a method of transforming this non-linear model into the linear one in real number field. Further, we simplify this method of nonlinear transformation to facilitate application. When we employ our model to analyze financial data, we find that both the goodness of fit and prediction ability is greatly improved.
机译:在本文中,我们研究了如何基于模糊积分(Choquet Integral或)IPO IPO)的非线性多元回归模型来研究如何估算非线性多元回归模型,然后提出一种将该非线性模型转换为线性的方法在实数字段中。此外,我们简化了这种非线性变换方法以便于应用。当我们使用我们的模型来分析财务数据时,我们发现既有契合和预测能力的良好都会大大提高。

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