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A Monte Carlo simulation study on Choquet integral with respect to different fuzzy measures

机译:Choquet积分关于不同模糊测度的蒙特卡罗模拟研究

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In this paper, a hybrid method based on Monte Carlo simulation study method and 5-fold cross-validation MSE method is used, a simulation experiment is conducted for comparing the performances of a multiple linear regression model, a ridge regression model, and the Choquet integral regression model with respect to three well known fuzzy measures, P-measure, λ-measure and L-measure, respectively. The result shows that the Choquet integral regression model with respect to L-measure outperforms other forecasting models.
机译:本文采用了基于蒙特卡洛模拟研究方法和五重交叉验证MSE方法的混合方法,进行了模拟实验,比较了多元线性回归模型,岭回归模型和Choquet的性能。分别针对三个著名的模糊测度(P测度,λ测度和L测度)的积分回归模型。结果表明,与L测度有关的Choquet积分回归模型优于其他预测模型。

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